Jobs ML / AI

We are looking for a talented Agentic Full stack Engineer (AI-Native Delivery) with 3+ years of commercial full stack experience, to join an established, revenue-generating B2B platform for the materials industry.

This is not a "write code with AI" role — it's an operate AI agents role: decompose work, fan it out to parallel coding agents, verify adversarially, ship across the stack.

JOB REQUIREMENTS:

Must have:

• 3+ years of commercial fullstack development experience (React + Node.js/TypeScript, or Python)
• Hands-on, practical experience directing multiple AI coding agents in parallel — isolated worktrees/branches, adversarial verification of agent output, spec-driven development, and building reusable AI skills/hooks/commands for recurring workflows 
• Working knowledge of PostgreSQL and basic understanding of cloud infrastructure (Terraform/AWS)
• Ability to work fully autonomously and communicate directly with an English-speaking client team without a manager in between
• English — Upper-Intermediate or higher

Nice to have:

• Experience with SAP / enterprise ERP integration (RFC/BAPI, ABAP, customer & order master data)
• Experience in multi-tenant / B2B SaaS platforms
• Familiarity with compliance frameworks (GDPR, SOC 2, ISO 27001)
• Experience building internal tooling for other engineers
• Design-system literacy

Key Responsibilities:

• Full-stack development across the client's platform — from a React component to a Postgres row-level-security policy to a Terraform module
• Cross-boundary root-cause debugging: auth, pagination, dependency conflicts, integration mismatches
• Turning recurring tasks into reusable AI agent skills, hooks, and commands so the next run is faster
• Proving results with concrete evidence — fixtures, payloads, read-back records — rather than relying on a green CI badge alone

PROJECT

Customer: Established, revenue-generating international platform for the materials industry, backed by a large global industrial distribution group.

Type: B2B SaaS / marketplace platform.

Product: The platform serves as a digital backbone for companies across the materials industry — chemicals, polymers, elastomers, rubber — replacing a patchwork of separate CRMs, ERPs, and spreadsheets with one connected system that turns commercial interactions and physical assets into structured, usable data.

Market: Global materials/chemicals industry, client team based in the US.

Stage: Mature, actively growing platform with an established engineering team (not a from-scratch build).

Project team: 3 developers, 2 QA, 1 DevOps on the delivery side, plus a dynamic client-side team. 

Work schedule: Full-time, full remote 

INTERVIEW STAGES:

• 1-st stage — Call with the Recruiter
• 2-nd stage — Interview with the technical specialist and the recruiter

• 3-rd stage —  Interview with the client

   

OUR BENEFITS:

• Projects with modern JS stack (React.js, React Native, Angular, Node.js)
• Strong JavaScript community at the company (90+ developers)
• Work from anywhere (fully remotely or in our office)
• Paid vacations and sick-leaves, additional days-off, relocation bonus
• Wellness: Medical insurance/ sport compensation/ health check-up+flu vaccination at your choice
• Education: regular tech-talks, educational courses, paid certifications, English classes
• Fun: own football team, budget for team-lunches, branded gifts
• One of the best IT employers in Lviv (or IT service companies in Ukraine) based on DOU rating

About the company

Are you tired of missing important moments in your weekly game because no one recorded you? Say goodbye to FOMO and hello to PUSHIT!

PUSHIT allows you to easily catch up on all the highlights you did while playing your sports game.

Our advanced replay system allows you to capture moments previously taken, so you never have to miss anything.

See those videos for more information about PUSHIT:

1. https://www.youtube.com/watch?v=uQrXgheKjCg
2. https://www.youtube.com/watch?v=pmdihAft2f8

See our current mobile apps:

1. IOS
2. Android

What is the job

You’ll be the Machine Learning Engineer on a compact, fast-moving team, working directly with the founders. Your mission: design, train, and ship computer-vision models that recognize sports events and generate highlight videos—running both in the cloud and on edge devices.

Responsibilities

• Build & improve CV models – object detection, action recognition, semantic segmentation, tracking, and event classification for multi-camera sports footage.
• Optimize for the edge – convert and quantize models (TFLite/ONNX/RT-Core) so they run in real time on Raspberry Pi 5 and ARM-based phones.
• Own the ML pipeline – data collection, labeling guidelines, experiment tracking (Weights & Biases / MLflow), automated training, and CI/CD to Kubernetes.
• Collaborate cross-functionally – work with backend, video-encoding, and mobile teams to integrate inference results into our NestJS APIs and Flutter/Angular clients.
• Raise the bar – research state-of-the-art techniques, run ablation studies, author technical specs, and mentor future student interns.

Requirements

• Strong Python (3 yrs+) and deep-learning expertise with TensorFlow and/or PyTorch.
• Solid background in computer vision: convolutional nets, attention mechanisms, spatio-temporal models (e.g., I3D, SlowFast).
• Experience deploying models to mobile or edge hardware (TFLite, Core ML, TensorRT, or similar).
• Familiarity with Docker & Kubernetes workflows for scalable training/inference.
• Proven ability to turn research into production code: at least one project or product in the wild (GitHub, app store, or academic publication).
• Comfortable with version control, code reviews, agile tickets, and writing clear documentation.
• Passion for sports—or at least enough curiosity to spot a backhand winner or a slam-dunk replay!

• English—professional level (our dev team is global).

   

Bonus points

• Experience with video encoding pipelines (FFmpeg, HLS, RTMP) or real-time streaming protocols.
• Knowledge of AWS/GCP services for training at scale (SageMaker, Bedrock, Vertex AI).
• Skills in data annotation tooling or active-learning strategies to shrink labeling budgets.
• Background in satellite or aerial image segmentation, sign-language or face-recognition projects (great analogies to sports CV challenges).

• Love for open-source: contributions to CV libraries.

   

Why PUSHIT?

• Ship features that thousands of weekend athletes use every day.
• Work on cutting-edge CV problems with real-time performance constraints.
• Small team ⇒ huge ownership, zero bureaucracy.
• Fully remote
• Competitive salary, early equity, and budget for conferences & GPUs.

JustMarkets is a global fintech company delivering high-tech trading and investment solutions to millions of clients across 160+ countries since 2012.

We are hiring an AI Automation Specialist to build scalable, AI-driven systems for our global marketing operations.

You will identify manual and repetitive tasks across content, PR, performance, design, and localization, and replace them with smart, scalable automation. This is a hands-on, high-impact role: you will design the systems that let us launch campaigns faster, scale content globally at a low cost, and stay ahead of competitors through automated intelligence.

Responsibilities

• Map current marketing workflows to identify manual bottlenecks and automation opportunities
• Design, build, and maintain end-to-end automation pipelines (Make.com, n8n, Zapier, custom scripts/APIs) covering content and localization workflows, competitor and sentiment monitoring, and performance dashboards
• Write and optimize prompts for LLMs (OpenAI, Anthropic, and others) to produce consistent, on-brand, structured outputs
• Build custom AI agents (GPTs, Claude Projects, or similar) for tasks such as compliance checks, copy-editing, or creative brief generation
• Maintain clean, reliable data flows between Google Sheets, Airtable, CRM systems, and SQL databases
• Monitor, debug, and upgrade existing automations as APIs and tools evolve
• Train the marketing team to confidently use the tools and agents you build

Requirements

• 2+ years of hands-on expertise with automation platforms such as Make.com, n8n, or Zapier
• Practical experience with AI/LLM tools: OpenAI API, Anthropic API, and vector databases or frameworks like LangChain or Flowise
• Experience with web scraping tools (BeautifulSoup, Scrapy, Selenium, or cloud scrapers like Apify)
• Solid understanding of REST APIs, webhooks, JSON, and OAuth authentication
• Strong prompt engineering skills, with the ability to produce consistent, structured outputs from LLMs
• A natural "how can I automate this?" mindset — you enjoy finding creative solutions to manual, repetitive problems
• Ability to explain technical concepts to non-technical colleagues in clear, business-focused language
• An analytical approach — you build automations to solve real problems and can measure their impact
•  Upper-Intermediate English level

We offer

• The opportunity to shape how AI and automation are used across an entire marketing department, from scratch
• Freedom to experiment with a wide range of tools, models, and frameworks to solve real business problems
• Tax expenses coverage for private entrepreneurs in Ukraine
• Expert support and guidance for Ukrainian private entrepreneurs
• 20 paid vacation days per year
• 10 paid sick leave days per year
• Public holidays as per the company's approved Public holiday list
• Medical insurance
• Opportunity to work remotely
• Professional education budget
• Language learning budget
• Wellness budget (gym membership, sports gear, and related expenses)

About ByChat FinOps

ByChat FinOps is a production-ready B2B AI platform that helps organizations understand, analyze, and optimize cloud infrastructure costs across AWS.

Our platform combines cloud billing data with Generative AI, enabling users to ask natural language questions such as:

• Why did our cloud costs increase this month?
• Which services generate the highest expenses?
• Will we exceed our budget next quarter?
• Where can we reduce infrastructure costs?
   

Behind the scenes, intelligent LLM Agents work with cloud APIs, read-only SQL queries, billing datasets, forecasting models, anomaly detection algorithms, and FinOps analytics to deliver accurate, explainable business insights.

ByChat FinOps is an actively growing production product where AI reliability, security, scalability, and measurable business value are our highest priorities.
 

About the Role

We are looking for a Senior / Lead ML Consultant to support our engineering team on a part-time basis and provide expert guidance on the architecture, development, evaluation, and optimization of our AI/ML capabilities.

This is primarily an advisory and technical leadership role rather than a full-time hands-on engineering position.

You will work closely with our AI/ML engineers and technical team, review existing approaches and processes, identify potential risks and inefficiencies, and provide practical recommendations for improving the quality, reliability, and efficiency of our AI systems.

We expect you to act as a senior technical advisor and sparring partner for the team, helping us validate technical decisions and ensure that our ML/LLM practices meet production-grade standards.
 

What You'll Do

Your responsibilities will include:

• Review the architecture and implementation of our AI/ML and LLM-based solutions.
• Provide regular technical feedback to AI/ML engineers and help validate key engineering decisions.
• Review existing ML/LLM development processes and recommend improvements.
• Evaluate the effectiveness, reliability, and scalability of current AI workflows.
• Advise the team on the design of LLM Agents, sub-agents, tool calling, structured outputs, and agentic workflows.
• Review approaches to prompt engineering, context management, guardrails, validation, retries, and hallucination mitigation.
• Assess and improve LLM evaluation methodologies, automated testing, golden datasets, and quality metrics.
• Advise on AI observability, tracing, monitoring, and production quality control.
• Review Text-to-SQL approaches and help ensure safe and reliable interaction with financial datasets.
• Provide guidance on anomaly detection, forecasting, and other ML components used within the platform.
• Identify performance bottlenecks and opportunities to optimize LLM latency, token usage, infrastructure usage, and operational cost.
• Help the team evaluate new AI/ML technologies, frameworks, models, and architectural approaches before introducing them into production.
• Participate in technical discussions and architecture reviews for complex AI-related features.
• Mentor engineers and help strengthen the team's ML/LLM engineering practices.
• Help establish practical engineering standards and best practices for building production-grade AI systems.
   

What We Expect

Must Have

• Strong senior-level commercial experience in Machine Learning / AI Engineering, ideally including technical leadership or consulting responsibilities.
• Proven experience designing and reviewing production AI/ML systems.
• Strong practical experience with modern LLM applications and Agentic AI systems.
• Deep understanding of:
  • LLM Agents and agentic workflows
  • Prompt Engineering
  • Function / Tool Calling
  • Structured Outputs
  • Context management
  • Hallucination mitigation
  • Guardrails and validation
  • Retry and fallback strategies
• Strong understanding of ML/LLM evaluation methodologies and how to measure AI system quality in production.
• Experience with AI observability, tracing, testing, and monitoring.
• Strong Python and SQL knowledge with the ability to review implementation and architecture decisions.
• Understanding of statistics, anomaly detection, forecasting, and data-driven system evaluation.
• Experience identifying technical risks, architectural weaknesses, and performance bottlenecks.
• Ability to translate complex technical findings into clear, practical recommendations for an engineering team.
• Strong communication and mentoring skills.
• English sufficient for technical discussions, documentation, and regular communication with the team.
   

Nice to Have

• Previous experience as a Lead ML Engineer, ML Architect, AI Architect, Staff/Principal ML Engineer, or ML Consultant.
• Experience with LangChain, LangGraph, or other Agent frameworks.
• Experience with AWS Bedrock, Claude, or other managed LLM platforms.
• Experience with FinOps, cloud billing, or cloud cost optimization.
• Knowledge of:
  • AWS CUR
  • AWS Cost Explorer
• Experience with Langfuse, LangSmith, RAGAS, or similar AI observability and evaluation platforms.
• Experience designing evaluation pipelines and golden datasets for LLM applications.
• Experience with forecasting and time-series analysis.
• Experience processing large financial or billing datasets.
• Understanding of multi-tenant architectures and secure AI tool execution.
• Experience optimizing LLM latency, token usage, and operational costs.
   

Technology Stack

• Python 3.12
• FastAPI
• LangChain
• LangGraph
• AWS Bedrock
• PostgreSQL
• SQL
• Langfuse
• RAGAS
• Docker
• Next.js / TypeScript
   

Engagement Format

• Part-time consulting engagement
• Flexible involvement based on project and team needs
• Regular technical reviews and consultations with the AI/ML team
• Architecture and solution reviews for key AI/ML initiatives
• Focus on technical guidance, quality assurance, process improvement, and mentoring rather than day-to-day feature implementation
   

Why Join Us?

• Influence the technical direction of a real production AI product without committing to a full-time role.
• Work on challenging problems at the intersection of Generative AI, Agentic AI, Cloud, and FinOps.
• Help shape the architecture and engineering practices behind production-grade AI systems.
• Work with a team that values measurable AI quality, reliability, security, and business impact.
• Apply your senior-level expertise where it has the highest impact: technical decisions, architecture, evaluation, optimization, and team development.
• Stay close to modern AI technologies while working in a flexible consulting format.

Looking for a Smart Contract Engineer 

Location: Remote / Anywhere
Start Date: ASAP
Engagement: Full-time, long-term (6+ months)
English: B2+
Interview Process: 1–2 rounds


About the Project
We are developing a cryptocurrency platform combining functionality across Ethereum and Solana.
The platform is inspired by Bustabit and Roobet Crash, featuring:

Rocket-style game chart similar to Roobet
Chat and player panel similar to Bustabit
Staking system
Referral system
Additional crypto-based features

Responsibilities

Own the deposit-lock smart contract on Solana and EVM — specification, development, deployment, and audit support.
Design the cross-chain settlement architecture together with the Protocol Engineer.
Develop comprehensive test suites using Hardhat and/or Foundry, including property-based fuzzing.
Work directly with external auditors, including Trail of Bits and OtterSec, throughout release cycles.
Follow smart contract security best practices and ensure production-ready implementations.

Requirements

Strong experience in smart contract development for EVM and/or Solana.
Hands-on experience with Solidity and relevant Solana smart contract technologies.
Strong knowledge of Hardhat, Foundry, or Truffle.
Experience with smart contract testing and property-based fuzzing.
Strong understanding of blockchain security and smart contract vulnerabilities.
Experience designing or implementing cross-chain protocols/settlement flows is highly desirable.
Experience working with security auditors is a strong plus.

Cloudfresh ⛅️ is a Global Google Cloud Premier Partner, Zendesk Premier Partner, Asana Solutions Partner, GitLab Select Partner, Hubspot Platinum Partner, Okta Activate Partner, and Microsoft Partner.

Since 2017, we’ve been specializing in the implementation, migration, integration, audit, administration, support, and training for top-tier cloud solutions. Our products focus on cutting-edge cloud computing, advanced location and mapping, seamless collaboration from anywhere, unparalleled customer service, and innovative DevSecOps.

We're looking for an AI Architect to become our lead technical expert for client AI solutions and to help stand up our AI Competence Centre and internal AI Lab.

This is a client-facing technical role first, with a build-and-lead dimension. Expect roughly 60% solution architecture and pre-sales engineering for enterprise clients, and 40% establishing the AI Lab and mentoring engineers. You'll technically lead and raise the bar for the team - this is a technical leadership role, not a people-management line.
Reports to: Head of AI.

Requirements

• Experience & seniority. 5+ years in software, data, or ML engineering, including 3+ years delivering ML/AI in production and 2+ years in a client-facing architect or technical lead capacity.
• Cloud & AI infrastructure. Production-level experience on Google Cloud Platform, especially the Vertex AI suite, plus integrating third-party model providers such as Anthropic.
• GenAI engineering. Strong hands-on knowledge of RAG, agentic workflows, orchestration frameworks (LangChain, LlamaIndex), vector databases, and prompt/context engineering.
• Production & MLOps. Hands-on with the ML lifecycle, CI/CD for models, automated deployment, and cloud cost management - including right-sizing models (lighter vs. heavier) to control spend.
• Evaluation, guardrails & observability. Practical experience building LLM evaluations, guardrails, and monitoring for accuracy, safety, latency, and cost in production.
• AI governance & security. Familiarity with data governance, model risk, and EU regulation (EU AI Act, GDPR) as it applies to enterprise AI — we're primarily EU-based.
• Pre-sales & client experience. Proven experience presenting to enterprise clients, scoping technical projects, and translating complex AI concepts into clear business value.
• Technical leadership. Experience guiding engineers, reviewing architecture and code, and raising team capability.
• Languages. Native Ukrainian — required, as you'll run Ukrainian-language pre-sales — and strong English (B2+/C1 minimum).

• Mindset & agility. An intrapreneurial drive to build an AI Lab from scratch inside an established business, plus the agility to move smoothly between client pre-sales and deep technical architecture.

   

Responsibilities

• Solution architecture. Design and own end-to-end AI systems for strategic enterprise clients - reference architectures, data and retrieval pipelines, agentic layers, and integration with existing enterprise systems - with a clear path from prototype to scalable, secure, observable production.
• Pre-sales & consulting. Partner with sales to qualify and win AI opportunities: run technical discovery, scope solutions, size effort and cost, and translate AI into business value, ROI, and risk for C-level stakeholders.
• Technical leadership & mentorship. Set architecture and engineering standards, run design and code reviews, and level up engineers across the AI practice.
• AI Lab & R&D. Stand up and run the internal AI Lab - rapid client prototypes and cost-effective internal AI tooling - with a clear bar for what graduates into production.
• Partner collaboration. Work with our core AI partners (Google Cloud / Vertex AI, Anthropic) to build joint solutions, access early capabilities, and shape our technical roadmap.
• Governance, security & cost. Build guardrails, evaluation, and observability into every solution; keep architectures compliant (EU AI Act, GDPR) and cost-aware through right-sized model selection.

Would be a plus

• Google Cloud Professional Machine Learning Engineer and/or Professional Cloud Architect certification.
• Hands-on enablement or certification with Anthropic and Vertex AI generative-AI stacks.
• Direct experience mapping solutions to the EU AI Act risk framework.
• Fine-tuning, distillation, or model-optimization experience.
• Production experience with voice/multimodal AI (e.g., ElevenLabs) or AI-assisted engineering tooling (e.g., Cursor).
• Contributions to the open-source GenAI ecosystem.

Work conditions

• Flexible Work Format: Work remotely, allowing you to balance your professional and personal life efficiently.
• Training with Leading Cloud Products: Access in-depth training on cutting-edge cloud and AI solutions, enhancing your expertise and equipping you with the tools to succeed in an ever-evolving industry.
• International Collaboration: Work alongside A-players and seasoned professionals in the cloud industry.
• Global Exposure: Expand your expertise by engaging with international markets across the EMEA and CEE regions.
• Vibrant Team Environment: Be part of an innovative, dynamic team that fosters both personal and professional growth, creating opportunities for you to advance in your career.
  
  When applying to this position, you consent to the processing of your personal data by CLOUDFRESH for the purposes necessary to conduct the recruitment process, in accordance with Regulation (EU) 2016/679 of the European Parliament and of the Council of April 27, 2016 (GDPR).
  Additionally, you agree that CLOUDFRESH may process your personal data for future recruitment processes. You can withdraw this consent at any time.

We are looking for an AI Integration Engineer (Python) to join our client's team on a UK insurtech project. 

Responsibilities: 

• Configure and deploy product journeys on the platform for each carrier or MGA partner 
• Build and maintain integrations with policy admin systems, quoting engines, and data feeds 
• Own data mapping and schema translation between the platform's data model and each insurer's existing architecture 
• Spot recurring patterns across deployments and turn them into platform improvements 
• Conduct technical scoping for new insurer partnerships, defining feasibility and required effort 

• Help define what a genuinely good AI insurance journey looks like in production 

   

Requirements: 

• At least 4+ years of hands-on experience with API integration and data mapping — real integration work 
• Strong Python experience, with a solid API/integration background 
• Insurance, insurtech, or closely adjacent background — a real understanding of how carriers, MGAs, and intermediaries operate 
• Day-one fluency with agentic tooling such as Claude Code, LangGraph/LangChain, or equivalent — not necessarily building pipelines from scratch, but able to hit the ground running 
• Comfortable being client-facing — equally at ease in a carrier meeting and in a terminal, sometimes in the same afternoon 
• A proactive mindset: someone who gets frustrated when a platform limits what they can deliver for a customer, and takes action to fix it 
• Upper-Intermediate English or higher 

We Offer:   

• Innovation Culture: Work in a team that actively experiments with AI and modern development approaches   
• Real Product Impact: Direct collaboration with a client and influence on product decisions   
• Flexible Work: Remote work or a modern office in Kyiv   
• Generous Time Off: 20 paid vacation days + 15 sick leave days annually   
• Professional Growth: Compensation for courses, certifications, and learning resources   
• Cutting-Edge Tools: Access to premium AI tools (Cursor Pro, Сlaude Code, GitHub Copilot, etc.)  

Recruitment Process:   

1. HR Interview   
2. Technical&Final Interview  
3. Client Stage 
4. Job Offer 

Company Overview

Robots & Pencils is an applied AI engineering firm building the next frontier of business architecture. We design and ship AI co-workers that integrate into enterprise operations and deliver measurable results for our clients. We're all in on AWS, combining deep UX capability with senior engineering talent to get AI into production fast and keep it there.
We’ve earned the trust of leaders across Consumer Products and Retail, Education, Energy, Financial Services, Healthcare, and Manufacturing and more, and earned a reputation as the nimble alternative to traditional global systems integrators. Founded in 2009, with delivery centers in Canada, the United States, Eastern Europe, and Latin America, we are smaller, faster, and more senior by design. Our teams average 15+ years of experience. We move fast, sweat the details, and build things that actually ship.
 

Position Overview

We’re looking for a Principal AI Engineer to define and drive the technical direction of our AI/ML systems. This role is ideal for a deeply experienced engineer who leads from the front — shaping architecture at the system level, solving the hardest problems, and raising the bar for how AI gets built and operated across the organization.

In this role, you will work on a cross-functional team, setting AI architecture standards, leading complex system design and implementation challenges, and solving integration problems that require both deep expertise and broad systems thinking. You’ll partner closely with leadership to define the AI roadmap and make high-stakes technical decisions that shape how our AI work scales across clients and over time.

Why This Role Matters

At Robots & Pencils, we design AI systems for a human world. Our name says it all. Robots and pencils means engineering paired with creativity, because every agent we ship has to work for real people in real workflows. That balance is baked into how we operate.

Every role here contributes directly to that mission. Here, you shape how AI systems integrate into enterprise operations, how teams move at real velocity, and how products create measurable impact for clients and the people they serve. We ship production-ready AI in 30 to 45 days. That pace demands people who take ownership, lead with craft, and care deeply about what they put their name on.

What You’ll Do

Craft & Delivery

• Define AI architecture and technical strategy, and lead implementation across the full lifecycle from design through production
• Build scalable ML platforms, pipelines, and workflow orchestration that support model development and event-driven, asynchronous operations at scale
• Architect and build LLM-powered systems, including prompt engineering, function/tool calling, multi-agent orchestration, RAG patterns, vector databases, embeddings, and streaming responses
• Design and develop APIs and backend services that integrate AI capabilities with enterprise systems and third-party platforms
• Lead model development, optimization, and the path from research to production, ensuring promising approaches translate into reliable, production-ready systems
• Ensure AI reliability, security, and scalability across deployed systems, including logging, monitoring, and debugging in production environments
• Bring an AI-forward mindset to your daily work, using tools like Claude, Cursor, and other modern AI assistants to ship higher-quality work at pace

Collaboration & Communication

• Co-define the AI roadmap with leadership, operating as a peer in strategic technical conversations
• Communicate complex technical concepts clearly to engineering and non-engineering stakeholders alike, translating depth into decisions others can act on
• Engage with product, engineering, and data teams to align AI work with broader business priorities

Leadership & Influence

• Define and champion AI engineering standards that shape how the organization builds and operates AI systems
• Mentor across the organization, shaping engineering culture and developing the next generation of technical leaders
• Own high-stakes architectural decisions that carry significant organizational and cross-engagement weight
• Drive technical vision — defining not just what gets built, but how AI engineering evolves at R&P over time

What You’ll Bring

• 9+ years of professional software engineering experience, with 5+ years focused on AI/ML systems in production and deep, hands-on expertise with generative AI development
• Expert software engineering background (Python or similar) with strong design sensibilities for distributed, scalable, and maintainable systems
• Deep experience designing distributed systems and event-driven architectures that underpin production AI workloads
• Deep expertise with cloud platforms, with mastery of AWS services and AWS GenAI offerings
• Proven track record architecting and shipping complex agentic systems in production across multiple teams or engagements
• Mastery of AI frameworks and orchestration tools, with clear judgment on when to adopt versus build
• Deep experience with evaluation frameworks and observability tools for LLM apps, including establishing these practices where they don't yet exist
• Deep expertise in AI safety, responsible AI principles, prompt injection defenses, PII handling, and AI governance and compliance in production
• Extensive experience designing RAG architectures: chunking strategies, embedding models, vector databases, and advanced retrieval techniques
• API and systems design experience, including architecting and integrating with internal and third-party services at scale
• Advanced cost optimization expertise: token economics, caching strategies, model routing, quantization
• Strong working knowledge of Docker, Kubernetes, and cloud-native AI architecture patterns
• Expertise in MLOps and AI infrastructure, including model versioning, monitoring, deployment automation, and reproducibility
• Demonstrable, day-to-day usage and expert command of AI-forward coding tools such as Claude Code and Cursor
• Track record of technical leadership and mentoring at an organizational level, with influence that extends beyond the immediate team
• Excellent problem-solving and stakeholder communication skills, with the ability to navigate the most ambiguous technical and business challenges with sound judgment

You’ll Do Well Here if You Are

• A doer. You see something broken and fix it. You'd rather move on clarity than wait for certainty.
• A fast learner who knows you don't know everything. The AI landscape changes weekly. You're senior enough to know better and curious enough to keep learning anyway.
• Direct in a way that makes the work better. You give honest feedback. You'd rather have the hard conversation than blow smoke.
• Obsessed with craft. You know genius is in the details. You ship exceptional, not perfect, and you don't put your name on work you wouldn't stand behind.
• Built for ownership. You honor commitments, admit mistakes fast, and back your teammates when a decision costs something. No handoffs, no finger-pointing.
• All in. You treat clients' businesses like your own. You take the work seriously without taking yourself seriously.
• Resourceful when the budget, timeline, or team is tight. Constraints don't slow you down. They sharpen you.
• Glad to be in the room with people who care as much as you do. Our teams average fifteen-plus years of experience. We hire people who push each other to do better work.

We Offer

• 20 days of paid vacation.
• 15 days of unpaid vacation.
• All official public holidays off.
• 5 paid sick days without a doctor's certificate.
• Medical insurance.
• Military draft deferment (reservation) support.
• Cooperation under a gig-contract.

Job Summary

We are seeking a highly organized and detail-oriented professional to support project planning, execution, and control. This role combines the functions of a coordinator and junior project manager and requires strong communication skills, multitasking, and a proactive approach to problem solving.
The primary objective of this position is to ensure the smooth running of projects by coordinating teams, monitoring deadlines, maintaining documentation, and supporting communication with clients and stakeholders.

Key Responsibilities:
- Assist in planning and tracking project progress to ensure adherence to deadlines and key milestones.

- Communicating complex information in a clear and understandable manner.

- Communicating and collaborating with internal and external teams to ensure completion of tasks and alignment with project objectives.

- Monitoring data quality and promptly escalating risks or issues that may impact scope, timelines, or quality.

- Providing regular project updates to clients and stakeholders, aligning expectations, and ensuring transparency.

- Maintaining and updating key project documentation: budget reports, trackers, meeting minutes, delivery schedules.

- Monitoring production KPIs (speed, quality), conducting random quality checks to maintain consistent results.

- Identifying and escalating scope changes at client request to the appropriate internal teams.

- Organizing and conducting meetings with the team/clients to agree on goals, discuss issues, and discuss project status.

- Assisting in resolving project issues and optimizing work processes to improve efficiency.

Requirements:

- Higher education in business, IT, or a related field (preferred)
- Experience in project coordination, operations, or support
- Understanding of the project lifecycle and basic Project Management principles
- Excellent planning, organization, and multitasking skills
- Strong communication skills, ability to clearly communicate information
- Ability to handle risks and problems, results-oriented
- Experience with project management tools (JIRA, Trello, Asana)
- Skills in working with spreadsheets, reports, and calculations
- Mandatory language requirements

Fluency in English and Russian/Ukrainian (oral and written)
will be an advantage

• Experience in data annotation or markup;
• Understanding of Agile/Scrum, Kanban;
• Experience working with cross-functional teams;
• Basic knowledge of IT processes and software development.
   

Are you a Data Scientist with a love of LLMs, generative AI?

We are looking for a passionate Data Scientist to implement AI solutions aimed at achieving business goals.

This role offers the opportunity to work on cutting-edge AI adoption projects that helps to improve current business processes.
 

     You'll be a great fit if you have:

•  Strong Python Experience (2 year +);
• Experience with LLM , Diffusion models;
• Knowledge of Prompt engineering;
• Experience with Gen AI-related technologies such as LangChain and RAG;
• Experience with Neural Networks (Optional) ;
• Experience with NLP , Predictive analytics and Machine learning;
• Experience with Pandas;
• Experience with SQL, including experience with large datasets;
• Strong experience in statistics;

• Bachelor's degree in Computer Science or a related field.
   

  What you'll do:

• Develop AI agents that utilize LLM, RAG and langchain approach;
• Implement LLM and Diffusion models to boost business productivity;
• Utilize LLM (LLM Vision) to improve object detection, text classification and extraction;
• Create forecasting, recommendation, and classification models;
• Transform business challenges to AI applications.
   

     We ensure your growth with:

• Competitive salary fixed in USD;
• Flexible working schedule and fully remote work format;
• Paid vacation days and sick leave days ;
• Personal and professional development opportunities;
• Participation in building innovative projects from scratch using modern technologies;
• Team-building activities and corporate events;
• English classes and educational events.

We're looking for an engineer with hands-on experience building and evaluating GenAI services - from RAG and agentic reasoning systems to production-grade LLM deployments. You'll work closely with Frontend and Backend teams to bring AI agents into real products, with a strong focus on reliability, safety, and shipping working prototypes fast.

Hard Skills:

• Practical experience developing and evaluating GenAI services, including RAG systems, understanding of the "ReAct" (Reasoning + Acting) paradigm and Agentic RAG, LLM API integration, and prompt/context engineering, as well as training, fine-tuning, and deploying ML models in production environments.
• Knowledge of ML/GenAI frameworks: LangGraph or LangChain, PyTorch / TensorFlow, Hugging Face, OpenAI/Anthropic SDK.
• Practical commercial experience working with AI models via API (Gemini, Anthropic) and self-hosted models (Llama 3, Mistral, Mixtral), with an understanding of model differences based on functional/non-functional requirements (FR/NFR).
• Deep understanding of how LLMs interact with external APIs via Function Calling.
• Experience with vector databases, semantic search methods, and principles of database structuring and cleaning.
• Practical experience with at least one cloud platform (AWS, GCP, or Azure).
• Proficiency in Python and understanding of asynchronous programming.
• Understanding of the AI model lifecycle: monitoring, versioning, and quality evaluation (RAGAS, DeepEval), with hands-on experience using these tools.
• Experience with Guardrails: setting hard constraints on conversation topics and agent actions, filters that automatically strip personal data before sending requests to external LLMs, and the ability to build output filters that fact-check generated responses before they're displayed.
• Deterministic Logic Integration — running AI agents on strict schemas to prevent the model from "making things up."
• A plus: knowledge of automated testing approaches for evaluating responses across large datasets to measure hallucination rates before MVP launch.
• Knowledge of Human-in-the-loop mechanisms, ensuring agents cannot execute actions without final user verification.
• Ability to design memory systems that store context from a client's previous conversations and operations for personalization (Long-term Memory & User Context).

Soft Skills:

• Ability to clearly communicate complex technical concepts and mentor team members.
• Ability to quickly test and evaluate new libraries and approaches.
• Analytical problem solving - debugging complex "black boxes" and understanding why an agent behaves unpredictably.
• Focus on delivering a working prototype rather than a perfect research paper.
• Close collaboration with Frontend and Backend developers to seamlessly integrate AI agents into the required environment.

We offer*:

• Flexible working format - remote, office-based or flexible
• A competitive salary and good compensation package
• Personalized career growth
• Professional development tools (mentorship program, tech talks and trainings, centers of excellence, and more)
• Active tech communities with regular knowledge sharing
• Education reimbursement
• Memorable anniversary presents
• Corporate events and team buildings
• Other location-specific benefits

*not applicable for freelancers

🔹 100% remote | 🌎 Global team | ⏳ Full-time

NineTwoThree AI Studio is a premier product design, engineering, and marketing firm specializing in custom AI, web, and mobile applications for established brands and funded startups. We are based in Massachusetts but with an American and European staff and a strong, collaborative remote culture.

We’re a team that loves doing good work with great people. Our relatively small size keeps us fast and nimble. The wealth of knowledge, experience and talent paired with proven recipes and best practices allows us to find opportunities to help new products succeed.

With a portfolio of over 150 launched products over 13 years, NineTwoThree has garnered recognition as a top AI agency in the U.S., earning accolades such as inclusion in the Inc. 5000 list for four consecutive years and being named among the top 50 AI firms alongside industry leaders like Microsoft, NVIDIA, and IBM. We’ve built AI and ML tech for big brands like Consumer Reports, FanDuel, and Nara, as well as startups in legal tech, logistics, education, and more. 

Role Overview

As a Senior ML Engineer at NineTwoThree AI Studio, you will sit at the intersection of production-grade software engineering, advanced natural language processing, and client delivery. We build custom, high-impact AI systems for brands and startups across diverse industries (such as healthcare, logistics, and fintech).

Instead of siloed academic research, this role demands a product-minded builder. You will design, optimize, and deploy robust LLM applications, custom predictive analytics, and agentic workflows directly into our clients' software ecosystems, taking absolute ownership of features from prototype to production.

Technology Stack

• Core Frameworks & Arch: Transformer models, modern LLM APIs (Anthropic Claude, OpenAI, AWS Bedrock, etc.), Open-Source LLMs.
• Orchestration & Agentic Design: Experience designing LLM workflows, agentic systems, or retrieval pipelines using frameworks such as Langchain, LangGraph, LlamaIndex, or equivalent approaches.
• Data & Search: Vector databases (Pinecone, pgvector, Milvus, Qdrant, etc.), SQL, and data engineering pipelines.
• Traditional ML: Supervised and Unsupervised learning (Classification, Regression, Anomaly Detection).
• Cloud & Infrastructure: AWS (Lambda, SageMaker, Bedrock, EC2) and modern DevOps/retraining pipelines.
• Languages: Production-grade Python.

Responsibilities

• Architect & Build AI Features: Design and implement robust classical ML and generative AI solutions, striking the right balance between autonomous agentic architectures and deterministic pipelines.
• Evaluate: Design and maintain evaluation frameworks to measure AI quality, reliability, safety, and business impact before and after deployment.
• Integrate & Deploy: Partner closely with full-stack developers and DevOps to seamlessly integrate AI capabilities into client web and mobile applications using serverless architecture (e.g., AWS Lambda) or API endpoints.
• Optimize for Production: Refine prompts, system instructions, and chunking strategies to balance accuracy, latency, token consumption, and data privacy.
• Traditional Predictive Analytics: Clean and process unstructured or historical client data to train/fine-tune custom algorithms for specific business problems (such as forecasting, classification, or anomaly detection).
• Collaborate & Communicate: Actively participate in client discovery sessions, translate ambiguous business requirements into viable technical scopes, and demo prototypes directly to stakeholder teams.
• Maintain Engineering Excellence: Engage in constructive code reviews, implement rigorous validation patterns to test AI outputs, and contribute templates or runbooks to our internal AI knowledge base.

Technical Experience

• Proven Track Record: 3+ years of experience engineering software with a strong focus on machine learning and natural language processing.
• LLM & Generative AI Mastery: In-depth understanding of modern LLM architectures, context window mechanics, semantic search techniques, and the limitations of generative systems. Ability to identify when a deterministic solution is preferable to an LLM or agent-based solution.
• Production experience: Experience building and operating production AI systems, including monitoring, evaluation, debugging, and iterative improvement.
• Evaluation experience: Understanding of evaluation methodologies for LLM-based systems, including retrieval quality, hallucination detection, and task-specific performance measurement. Ability to reason about tradeoffs between quality, latency, cost, reliability, and engineering complexity.
• Python & SQL Proficiency: Exceptional Python coding skills and the ability to query, clean, and structure data efficiently.
• Cloud Infrastructure: Hands-on experience deploying ML or API services within cloud ecosystems, preferably AWS.
• Ownership: Comfortable taking ownership of ambiguous problems from initial discovery through production deployment and ongoing support.

Product & Team Capabilities

• Ambiguity to Execution: Ability to drop into a completely new industry vertical, understand its data constraints, and spin up a working proof-of-concept within a few weeks.
• The "Product Engineer" Mindset: Passion for seeing things ship and understanding why something is being built from a business value standpoint, not just what is being built.
• Communication: Fluent written and spoken English. Comfortable interacting with client stakeholders and breaking down technical workflows into clear concepts.
• Adaptability: Eagerness to experiment with and evaluate fast-emerging AI development tools, models, and frameworks.
• Education: Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or a related field (or equivalent practical experience).

What We Offer

• Annual paid vacation: 20 days off per year during the first 3 years, increasing to 25 days in later years
• Paid sick leave, 10 national holidays, and 2 company days off
• Well-being budget
• Global health coverage 
• Maternity/paternity leave
• Reimbursement of expenses for professional development courses and certifications (up to 100% in agreement with Manager)
• Strong positive engineering culture, a tightly-knit team of professionals with a good sense of humor

What's The Process

We value your time and ours and make the process fast and easy. Our interview process takes the following steps: a short interview with the HR, 2nd technical interview with ML Engineer and CTO (optional), 3rd live-coding interview, Offer.

Automat-it is an all-in AWS Premier Partner and Managed Services Provider specializing in the startup ecosystem. With over 800 customers and 500+ AWS certifications, Automat-it brings hands-on expertise in AI, DevOps, and FinOps to empower fast-paced startups to grow, deliver & win. Our customers save significant time-to-market and optimize their cloud performance and costs.

We work across EMEA and the US, fueling innovation and solving complex challenges daily. Join us to grow your skills, shape bold ideas, and help build the future of tech.

We’re looking for an AI Engineer (Senior level or strong Middle) to join our team and work directly with startup's Data Science and R&D teams. This is a hands-on, delivery-focused role where you will own projects end-to-end, from early design to production deployment.

The role is focused on building production-grade Generative AI systems on AWS, especially RAG pipelines, agent-based workflows, and LLM-powered backend services. This is not a pure research or model training role, it’s about designing and shipping reliable systems under real constraints.

📍 Work location: remote from Ukraine.

If you are interested in this opportunity, please submit your CV in English.

Key Responsibilities

• Build and deliver production-ready GenAI systems on AWS, including RAG pipelines, retrieval logic, and LLM-based services
• Design and implement agent-based or multi-step workflows for real use cases (not just prototypes)
• Work closely with Solution Architects, DevOps, and client teams to turn ideas and POCs into scalable systems
• Deploy, monitor, and improve ML/LLM systems in production, focusing on performance, cost, and reliability
• Work with AWS services such as Bedrock, OpenSearch, Lambda, S3, DynamoDB, SageMaker, and CloudWatch
• Adapt existing ML or GenAI code into production environments when needed
• Continuously improve system quality, including retrieval performance, output consistency, and evaluation approaches

• Operate in a fast-paced, project-based environment where you may own a project as the main engineer

   

Requirements

• Strong hands-on experience building and deploying AI / GenAI systems in production
• Solid experience with AWS in real projects (not just Console usage), including working with services like Bedrock, OpenSearch, Lambda, S3, or similar
• Experience building RAG systems in practice, including retrieval logic, vector databases, and output quality improvements
• Experience working with LLM frameworks or tools such as Amazon Bedrock, OpenAI, LangChain, or LlamaIndex
• Strong Python skills and a good understanding of backend system design
• Experience designing multi-agent systems or more complex orchestration workflows
• Experience with vector databases (OpenSearch, pgVector, Pinecone, etc.)
• Comfort working in fast-moving environments with short project cycles (weeks to a few months)
• Strong communication skills and ability to work directly with clients and cross-functional teams
• Ability to clearly explain technical decisions, limitations, and trade-offs in English (written and spoken)
• Experience with AWS Bedrock advanced features (e.g. Knowledge Bases, agent orchestration) - an advantage 
• Experience with Kubernetes, Docker, IaC Terraform and CI/CD pipelines  - an advantage 

• Background in Machine Learning or Data Science (including model training or fine-tuning)  - an advantage

   

What Success Looks Like in Year One

• Within 12 months, you are independently owning and delivering production GenAI systems on AWS, from initial design through deployment and iteration
• Working directly with customers and making clear architectural decisions around performance, cost, and reliability

• You are comfortable taking an ambiguous problem, turning it into a working system end-to-end, and explaining the trade-offs behind your approach

   

Why Join Automat-it?

Be at the Forefront of Cloud Innovation

Join a global leader and AWS Premier Tier Services Partner. We don't just use the cloud; we master it. As an All-In AWS partner, you’ll work with the most sophisticated tech stacks and help maintain our status as a top-tier collaborator in the global ecosystem.

Work on Meaningful, Large-Scale Impact

We specialize in helping startups and scaleups scale at speed. By joining us, you’ll be part of a team that has successfully completed hundreds of complex projects, directly influencing the growth of the next generation of unicorns through our unique "Product-based Professional Services" approach.

Accelerate Your Career Trajectory

In our fast-paced, dynamic environment, "growth" isn't just a buzzword. You will have:

• Clear Progression: Defined career paths from engineering to leadership.
• Continuous Learning: Sponsored AWS certifications and access to internal "Expert-led" knowledge sharing.
• Cutting-Edge Exposure: Early access to beta AWS features and high-level architectural challenges.

Thrive in a Culture of Excellence

We pride ourselves on a collaborative, supportive, and transparent culture. You’ll work alongside and learn from some of the industry’s brightest architects and DevOps engineers who are committed to mentorship and collective success, including AWS Gold Jacket recipients.

Global Reach, Boutique Feel

With over 250 employees across EMEA and the USA, enjoy the stability of a mature, profitable company with the agility and spirit of a startup. Whether you are working on GenAI & Agentic use cases, DevOps automation, FinOps optimization, or Kubernetes migrations, your voice is heard, and your contributions are visible.

Benefits

• Professional training and certifications covered by the company (AWS, FinOps, Kubernetes, etc.)
• International work environment
• Referral program – enjoy cooperation with your colleagues and get a bonus 
• Company events and social gatherings (happy hours, team events, knowledge sharing, etc.)
• English classes
• Soft skills training

Country-specific benefits will be discussed during the hiring process.

Automat-it is committed to fostering a workplace that promotes equal opportunities for all. We firmly believe that cultivating a diverse workforce is crucial to our success. Our recruitment decisions are grounded in your experience and skills, recognizing the value you bring to our team.

At c3 we're building a spatial intelligence data layer. We're a startup based in the UK, and are building an engineering team to focus on research and development of our proprietary models. 

Ideally we are looking for someone with: 

Multi-session SLAM / map merging / long-term localization / 3D registration experience

Ideal past experience:

Autonomous-driving mapping, warehouse/robot localization, AR persistent maps, LiDAR map differencing, construction progress monitoring, digital twins, or long-term robotics localization.

Requirements

* Strong background in 3D computer vision and geometric perception: point clouds, meshes, depth maps, coordinate transforms, registration, visibility/occlusion reasoning, and spatial change detection.

* Hands-on experience with real RGB-D / LiDAR / depth-sensor data. You should have dealt with noisy depth, incomplete scans, moving objects, partial overlap, and sensor/calibration errors.

* Strong understanding of 3D registration, including ICP variants, robust/global registration, geometric descriptors, RANSAC/TEASER++-style approaches, and failure detection.

* Experience solving multi-session or temporal mapping problems: comparing the same physical environment captured at different times.

* Familiarity with SLAM / visual-inertial odometry. You should understand accumulated drift, scale error, loop closure, and how errors in scan generation propagate downstream.

* Strong Python and PyTorch skills, with experience building production-quality evaluation and inference pipelines.

* Experience with learned feature matching such as LightGlue, SuperGlue, LoFTR, or equivalent is useful, particularly for cross-scan registration.

* Experience with synthetic data generation / simulation for augmentation and controlled failure-case generation.

* Robotics, autonomous systems, mapping, AR/VR, drones, or defence perception experience is highly relevant.

* Fluent English.

* Kyiv-based preferred; hybrid or remote considered.

What you will do

* Build a robust scan0 -> scan1 registration pipeline that aligns mostly-static structure while remaining insensitive to moved furniture and other transient objects.

* Handle partial overlap, occlusion, missing observations, drift, and scale differences between scans.

* Build temporal change detection that distinguishes:

    * object removed / added,

    * object moved,

    * surface or condition changed,

    * area unchanged,

    * area not observable / insufficient evidence.

* Develop visibility and free-space reasoning so that “not seen” is not incorrectly classified as “gone.”

* Build multi-stage registration using geometric and learned features, followed by robust local refinement.

* Define confidence / failure detection for registration and comparison results rather than forcing a result from bad scans.

* Develop condition/defect classification and severity scoring once geometric correspondence is sufficiently reliable.

* Create synthetic perturbations and generated training/evaluation data covering known failure modes.

* Own evaluation against ground truth, including registration success rate, false positive/negative change detection, localization accuracy, and uncertainty calibration.

* Evaluate alternative scene representations, including 3D Gaussian Splatting, NeRFs, TSDFs, occupancy/SDF representations, where they materially improve temporal comparison.

Title: AI Engineer
Reports to: Principal AI Architect
Department: AI & Advisory
Location: Ukraine – Remote
Term: Full-Time

About Atlas Technica

Atlas Technica’s mission is to shoulder IT management, user support, and cybersecurity for our clients, who are hedge funds and other investment firms. Founded in 2016, we have grown year over year through our uncompromising focus on service.

We value ownership, execution, growth, intelligence, and camaraderie. We are looking for people who share our Core Values, thrive, and contribute to this environment while putting the customer first. At Atlas Technica, we offer a competitive salary, comprehensive benefits, and great perks to our global Team. We strive to maintain a professional yet friendly environment while promoting professional and career development for our Team Members. Join Atlas Technica now!

Position Overview

We are seeking an AI Engineer to join our growing AI & Advisory team in Ukraine. This is a hands-on engineering role focused on building, integrating, testing, and deploying AI-enabled applications and enterprise solutions for sophisticated client environments.

Working under the technical direction of a Principal or Senior AI Architect, the AI Engineer will translate approved architecture and security decisions into working software, integrations, deployment patterns, tests, and technical evidence. This role will build rapid proofs of concept while also helping move successful solutions toward secure, maintainable, and supportable production use.

The successful candidate will combine strong software engineering fundamentals with practical AI, Azure, integration, and security experience. This is not a research-only or prompt-engineering role; we are looking for an engineer who enjoys writing production-quality code, solving complex integration challenges, testing assumptions, and delivering reliable technical solutions.

Position Responsibilities:

• Build rapid proofs of concept and production-ready components for AI-enabled research, data access, document analysis, workflow automation, reconciliation, and internal application use cases
• Develop, review, refactor, test, and maintain application code using Python and other supported development technologies
• Build and integrate REST APIs, MCP components, connectors, webhooks, databases, enterprise applications, and data-integration services
• Connect AI-enabled workflows with Microsoft 365, SharePoint, Microsoft Graph, enterprise data stores, third-party platforms, and approved AI services
• Implement retrieval and data-processing solutions using embeddings, vector or hybrid search, metadata filtering, indexing, and access-aware patterns
• Deploy and operate applications within Microsoft Azure using approved hosting, identity, storage, database, networking, security, and deployment patterns
• Build repeatable development and release processes using Git, CI/CD, Docker, automated testing, and infrastructure automation
• Implement appropriate authentication, authorization, role-based access, secrets management, logging, monitoring, environment separation, and other security controls
• Test AI solutions for reliability, security, model failure, prompt injection, inappropriate data access, unsafe tool use, dependency failure, and other production-readiness risks
• Participate in architecture reviews, code reviews, client technical sessions, troubleshooting, production-readiness assessments, and technical handoffs
• Maintain clear implementation documentation, diagrams, runbooks, testing evidence, and technical decisions while proactively communicating blockers, scope changes, and delivery risks
• Contribute reusable code, deployment templates, testing approaches, connector patterns, and engineering standards to Atlas Technica’s Ukraine-based AI capability

Requirements:

• 5+ years of professional software engineering experience, including recent hands-on work with AI-enabled applications, cloud applications, data systems, or enterprise integrations
• Strong Python development skills with experience building APIs, services, scripts, applications, or data workflows
• Experience with at least one additional production development stack such as C#/.NET, TypeScript/Node.js, Java, or a comparable technology
• Hands-on Microsoft Azure experience across application hosting, identity, storage, databases, secrets management, logging, monitoring, and deployment
• Practical experience with LLM APIs, agentic workflows, retrieval-augmented generation (RAG), embeddings, structured outputs, prompt design, and model limitations
• Experience building or integrating APIs, connectors, MCP components, databases, data platforms, or enterprise workflow systems
• Strong understanding of authentication, authorization, role-based access control, least privilege, environment separation, and secure secrets management
• Experience with Git, CI/CD, Docker, automated testing, production troubleshooting, and modern software-development practices
• Ability to write clean, maintainable, and testable code and clearly explain technical and implementation decisions
• Strong problem-solving, ownership, documentation, and follow-through skills with the ability to work effectively in a remote and collaborative delivery environment
• English proficiency at B2 level or higher, with the ability to participate effectively in technical client discussions and produce clear written documentation

Desirable Qualities:

• Experience with Azure AI Foundry, Azure OpenAI, Azure AI Search, Microsoft Agent Framework, or comparable AI orchestration technologies
• Experience with Microsoft Graph, SharePoint Online, Microsoft Entra ID, Microsoft 365, Copilot Studio, or Power Platform
• Experience with technologies such as Azure Functions, Azure Container Apps, App Service, Azure SQL, PostgreSQL, Cosmos DB, Snowflake, or similar data and application platforms
• Experience developing evaluation datasets, regression tests, or other approaches for testing non-deterministic AI components
• Experience moving prototypes, internally developed applications, vendor solutions, or citizen-developed applications toward controlled production use
• Experience supporting financial services, regulated industries, enterprise clients, or other environments with strong security and compliance requirements
• Relevant Microsoft Azure, AI, software engineering, or cloud certifications
• Experience creating reusable engineering patterns, mentoring junior engineers, or contributing to engineering standards and technical knowledge sharing