Jobs ML / AI

Reelly AI is a B2B platform in the real estate sales sector that has become one of the market leaders in the UAE in just four years. More than 74,000 agents have registered on the platform. We help them find up-to-date information on more than 2,000 projects from developers in Dubai, Abu Dhabi, and Ras Al Khaimah.

Our business is selling data and access to our proprietary AI ecosystem. It helps developers see supply and demand in real time, understand agents’ needs, and make commercial decisions faster.

We work with international companies, including those from India, Pakistan, and the United Kingdom, that operate in the UAE. We are preparing for international expansion in cooperation with government partners. Our goal is to attract one million agents over the next three years.

I am writing this job posting personally. My name is Vitalii Ryzhak, and I am the founder and CEO of Reelly AI.

Recently, the real estate market in the region has experienced significant stress. For us, this period has become a catalyst for growth: developers have started digitizing their processes more actively, and we have received a large influx of new contracts. That is why I am resuming the search for new talent to join our team.

We are looking for a hands-on Head of AI & Business Automation who will report directly to me, the CEO, and turn opportunities for internal automation into reliable systems that people use every day.

You will own the strategy, implementation, adoption, and measurable business results of AI automation across Sales, Support, Customer Success, onboarding, CRM, and data operations. You will personally build the first production agents and workflows, working with our CTO and Product team on architecture, security, and alignment with the customer-facing roadmap.

What you will do

• Map processes with their owners, identify bottlenecks, and establish a baseline for time, cost, errors, and service quality
• Prioritize an automation backlog by expected business value and effort; decide when to build, buy, or improve an existing process
• Build and launch agents, integrations, and workflows using APIs, webhooks, and company data; address data quality before scaling
• Make systems dependable: test output quality, monitor usage and costs, keep logs, handle failures and retries, and provide human review or handoff where needed
• Work with the CTO on safe data access, permissions, and security; choose straightforward rule-based automation when an LLM is unnecessary
• Help process owners adopt new workflows through documentation, training, and clear ownership; measure actual results after launch
• Manage priorities and ongoing reliability, and help recruit and lead a small team as needs become clear

Who we are looking for

• Someone who can show 2–3 production AI or automation cases used by real people, explain their personal contribution, and share before-and-after results
• Practical ability to build with Python or TypeScript, SQL, REST APIs, and CRM systems
• Good judgment about when to use an LLM, a deterministic workflow, or human involvement
• Experience delivering reliable business systems, with attention to data quality, access safety, testing, monitoring, and operating costs
• Someone who can independently work with technical and non-technical teams, explain trade-offs, and communicate clearly in English
• Strong ownership: you can turn an unclear business problem into a prioritized plan, ship a working solution, and measure its effect

Experience in B2B SaaS or a data/API business, Sales, Customer Success, Support, or leading a small team will be an advantage. Familiarity with n8n, Make, Zapier, MCP, or RAG is useful where it solves a real problem.

The first 90 days

We would expect you to establish process baselines and a prioritized backlog, launch an initial pilot, and work toward 2–3 production workflows with clear owners, monitoring, and measured results. We will agree on the scope and success measures together based on the opportunities you identify.

Why this role may interest you

• Direct collaboration with the founder and influence over decisions
• Working at a fast-growing product startup that is already a leader in the international market
• Experience in a field involving some of the world’s most expensive real estate, investments, AI, data, marketing, and rapid growth
• A high salary, bonuses, and company shares. Full transparency and a young team
• Opportunities for business travel: we have already launched operations in Thailand, Indonesia, the Maldives, Georgia, and other destinations

My recommendation:

If you want the opportunity to join our team, apply for this role on Djinni. Details of the next stage and an invitation to a call will be shared with applicants through Djinni. On this call, I will introduce you to our company and all the opportunities within it: our corporate culture, challenges, results, and possibilities.

I, Vitalii Ryzhak, will be speaking on this call, and my goal is to make you fall in love with our mission just as I did six years ago. I believe that only the strong win. And we are building our strength in attracting international capital so that, when the time is right, we can focus all our efforts on rebuilding Ukraine.

Glory to Ukraine! Glory to the Heroes!

On behalf of our Client, Mobilunity is looking for a Senior AI / ML Engineer.

Our client is a high-growth, award-winning African nonprofit on a mission to radically transform healthcare access. The organization works to strengthen the potential and resilience of adolescent girls across Africa by building local health ecosystems that provide stigma-free, no-cost, quality-assured healthcare services.

Their technology platform connects community organizations, healthcare providers, and retail partners by enabling referrals, verifying service delivery, facilitating payments, and generating real-time data.

The organization operates across Kenya, Ethiopia, Uganda, Burkina Faso, South Africa, and Nigeria, with additional offices in Portugal, the Netherlands, and the United Kingdom. The global team consists of more than 250 international colleagues and works in a fast-paced, informal, and collaborative environment.

The role focuses on one of the organization’s critical scaling challenges: risk and fraud on the platform. It combines strong software engineering and data infrastructure skills with deep hands-on experience building and deploying modern AI and LLM-based systems in production.

Key Responsibilities:

Agentic Systems & GenAI Engineering

• Design, deploy, and debug sophisticated agentic AI workflows with multi-step reasoning, memory integration, and Model Context Protocol (MCP).
• Build and operate multi-agent systems using LangGraph, LangChain, or equivalent frameworks.
• Architect and continuously improve Retrieval-Augmented Generation (RAG) pipelines, including chunking strategies, retrieval mechanisms, and end-to-end evaluation.
• Deploy and operate LLM-based services in production.
• Optimise LLM systems for latency, throughput, reliability, and cloud costs using technologies such as LiteLLM, vLLM, SageMaker, or Bedrock.

Production ML & Engineering

• Develop traditional machine learning models for structured data, including classification, regression, ranking, and/or NLP use cases.
• Write clean, maintainable, production-quality Python code that integrates with the wider data and software engineering ecosystem.
• Work with large-scale structured datasets using complex SQL queries and data pipelines.
• Design and maintain evaluation and monitoring approaches for AI/ML systems.
• Contribute to team rituals, technical documentation, and shared engineering practices.
• Build systems with appropriate failure handling, monitoring, and graceful degradation.
• Take ownership of solutions from initial design through production operation and continuous optimisation.

Requirements:

• 5+ years of professional experience as an ML Engineer, Data Scientist, AI Engineer, Software Developer, or a similar role.
• Proven experience shipping and operating production software.
• Outstanding proficiency in Python.
• Strong experience working with large-scale structured data using SQL.
• Proven practical experience building and serving LLM-based or agentic AI systems for real users in production, rather than only developing internal prototypes.
• Hands-on experience with agent orchestration, multi-step AI workflows, or similar production GenAI systems.
• Solid understanding of traditional machine learning, with strong expertise in at least one area such as tabular ML, NLP, or deep learning.
• Strong understanding of production ML systems, including reliability, monitoring, evaluation, and optimisation.
• Strong verbal and written English communication skills.
• Ability to work independently, move quickly through iterative feedback loops, and take ownership of business outcomes.

Nice to Have:

• Experience in Risk, Fraud, Credit, Insurance, Cybersecurity, Fintech, or similar domains.
• Experience with GenAI observability, drift detection, and evaluation frameworks such as LangSmith, Evidently, or RAGAS.
• Hands-on experience with AWS environments and MLOps automation.
• Experience with containerisation and CI/CD for machine learning systems.
• Experience with LLM serving and optimisation using tools such as LiteLLM, vLLM, SageMaker, or Bedrock.
• Experience with LangGraph, LangChain, MCP, or multi-agent frameworks.
• Experience mentoring junior engineers or contributing to the wider technical community through blogging, talks, or public speaking.

N-iX is looking for a Senior Applied ML Engineer to support our client's Data Licensing team, which develops training datasets for frontier AI labs. You will evaluate and productionise existing ML models and services to deliver customer-requested metadata enrichment for data licensing opportunities, supporting the next generation of AI applications.

Responsibilities:

• Partner with the Principal Data Scientist and Principal Data Engineers, senior technical leaders and data scientists to implement and evolve model-evaluation and productionisation standards; independently own assigned enrichment workflows from evaluation through production delivery.
• Evaluate candidate models on representative content, using appropriate quality measures and threshold analysis to support selection and release decisions.
• Develop tested, maintainable Python inference components that conform to shared engineering frameworks, metadata contracts and deployment standards.
• Support ad-hoc metadata backfills by validating model outputs, estimating inference cost and throughput, and resolving model-specific processing issues.
• Work with data engineers to move enrichment components from representative evaluation to reliable corpus-scale execution.
• Assess model licensing, data-handling constraints and provenance requirements, ensuring enrichment outputs are reproducible and suitable for commercial use

Requirements:

• 6+ years of experience in applied ML, ML engineering, data science or software engineering, including hands-on experience delivering production ML inference systems.
• Experience evaluating pretrained or third-party ML models, defining appropriate quality metrics and operating thresholds, while balancing model quality against inference cost, throughput and operational complexity.
• Strong Python software engineering skills, including testing, packaging and dependency management.
• Hands-on proficiency with ML libraries and frameworks such as PyTorch, TensorFlow, scikit-learn or Hugging Face.
• Experience developing, deploying and maintaining high-performing, resilient and scalable ML inference systems across CPU and GPU environments in both AWS and GCP
• Experience troubleshooting and optimising model execution in distributed, cross-cloud workflows.
• Clear communication skills and experience building consensus with technical and commercial partners.

Nice to have:

• Model tracking and lifecycle tooling such as MLflow.
• Managed ML and batch-inference platforms such as SageMaker, Vertex AI or Databricks.
• Experience evaluating models for image, video or audio content.
• Experience with Snowflake, DBT or Clickhouse

N-iX is looking for a Senior Applied ML Engineer to support our client's Data Licensing team, which develops training datasets for frontier AI labs. You will evaluate and productionise existing ML models and services to deliver customer-requested metadata enrichment for data licensing opportunities, supporting the next generation of AI applications.

Responsibilities:

• Partner with the Principal Data Scientist and Principal Data Engineers, senior technical leaders and data scientists to implement and evolve model-evaluation and productionisation standards; independently own assigned enrichment workflows from evaluation through production delivery.
• Evaluate candidate models on representative content, using appropriate quality measures and threshold analysis to support selection and release decisions.
• Develop tested, maintainable Python inference components that conform to shared engineering frameworks, metadata contracts and deployment standards.
• Support ad-hoc metadata backfills by validating model outputs, estimating inference cost and throughput, and resolving model-specific processing issues.
• Work with data engineers to move enrichment components from representative evaluation to reliable corpus-scale execution.
• Assess model licensing, data-handling constraints and provenance requirements, ensuring enrichment outputs are reproducible and suitable for commercial use

Requirements:

• 6+ years of experience in applied ML, ML engineering, data science or software engineering, including hands-on experience delivering production ML inference systems.
• Experience evaluating pretrained or third-party ML models, defining appropriate quality metrics and operating thresholds, while balancing model quality against inference cost, throughput and operational complexity.
• Strong Python software engineering skills, including testing, packaging and dependency management.
• Hands-on proficiency with ML libraries and frameworks such as PyTorch, TensorFlow, scikit-learn or Hugging Face.
• Experience developing, deploying and maintaining high-performing, resilient and scalable ML inference systems across CPU and GPU environments in both AWS and GCP
• Experience troubleshooting and optimising model execution in distributed, cross-cloud workflows.
• Clear communication skills and experience building consensus with technical and commercial partners.

Nice to have:

• Model tracking and lifecycle tooling such as MLflow.
• Managed ML and batch-inference platforms such as SageMaker, Vertex AI or Databricks.
• Experience evaluating models for image, video or audio content.
• Experience with Snowflake, DBT or Clickhouse

We are looking for an experienced Principal AI Engineer to lead the architecture, technical strategy, and evolution of enterprise-scale AI platforms and GenAI-powered solutions. The role requires strong hands-on experience with production AI systems, RAG, AI orchestration, distributed platforms, and AI engineering standards.

Responsibilities

• Define and own the architecture of enterprise-scale AI platforms
• Design and develop production-grade GenAI systems and AI-powered solutions
• Lead the development of RAG pipelines, retrieval infrastructure, and AI orchestration frameworks
• Design scalable distributed systems, APIs, data pipelines, and event-driven architectures
• Establish standards for AI quality, evaluation, observability, governance, and model lifecycle management
• Define and scale AI-driven software-development practices, including tools, guardrails, and automation patterns
• Drive architecture decisions and technical alignment across multiple engineering teams
• Build reusable AI platform components, frameworks, and internal tooling
• Conduct architecture and code reviews and mentor senior and Staff-level engineers
• Collaborate with product, data, security, infrastructure, and engineering teams
• Document architectural decisions, technical standards, and organizational best practices

• Lead technical initiatives across distributed international teams

   

Requirements

• 12+ years of professional software-engineering experience
• Significant experience working at Staff or Principal Engineer level
• Strong hands-on experience building and deploying production-grade GenAI / LLM systems
• Expert-level Python engineering skills
• Strong experience with LLM applications, RAG, vector databases, and retrieval infrastructure
• Experience with LangChain, LlamaIndex, semantic search, or similar AI frameworks
• Strong understanding of AI evaluation, model lifecycle management, observability, and MLOps
• Proven experience designing and evolving large-scale distributed systems
• Strong knowledge of APIs, data pipelines, event-driven systems, and high-scale platforms
• Experience driving architecture and platform initiatives across multiple teams
• Hands-on experience with AI-assisted development tools such as Copilot, Claude Code, or Cursor
• Strong engineering fundamentals in code quality, testing, CI/CD, and observability
• Ability to influence technical decisions and drive alignment without formal authority
• Experience collaborating with distributed teams across different regions and time zones

• Professional English, Upper-Intermediate or higher

   

Nice to have

• Experience building enterprise AI platforms or internal AI developer platforms
• Experience with Kubernetes, cloud platforms, and infrastructure automation
• Experience with MLOps platforms and model monitoring
• Experience with event-driven architectures and large-scale data processing
• Experience establishing AI governance and engineering standards across organizations
• Experience working with distributed teams across the US, China, and LATAM
• Experience in enterprise SaaS, FinTech, healthcare, or other complex domains

We’re looking for an experienced developer to build an AI assistant that users can interact with through text messaging. The assistant will connect to our existing database, answer questions using our information, handle follow-up questions, and send personalized news updates based on users’ interests.

The experience we’re aiming for is similar to texting an assistant like Instinct or Muse, with a focused scope: answering questions using our existing database and delivering personalized news updates.
 

You’ll take ownership of the technical setup, integrations, and development, working with our team to launch an initial version. Our target is a working pilot within approximately one month, with the scope finalized together.
 

You should have strong Python/Django experience and hands-on experience integrating AI models, APIs, and databases. Experience with Twilio or similar messaging platforms is important, along with building secure account access, subscription permissions, and scheduled notifications.
 

We’re looking for someone who has built and launched practical AI applications and can make sound technical decisions, communicate clearly, and identify potential issues early. Accuracy is essential: the assistant needs to retrieve reliable information from our data and handle unclear questions appropriately.
 

When applying, please share examples of relevant applications you’ve built, explain your specific role, and describe the tools you used. Please also include your availability over the next month and your hourly rate or estimated project budget.

Are you energized by walking into a client’s operation, finding the workflow that’s actually holding them back, and rebuilding it so AI handles the parts that don’t need a person? At Sigma Software, we don’t just add AI on top of existing processes  we redesign how the work gets done, with AI built into the operating logic from day one.

We’re looking for a Forward AI Deployment Engineer to own that redesign end to end: embedded with the client, hands-on with whatever automation the workflow actually needs, and accountable for turning a real operational problem into something running in production not a demo, not a pilot. Each engagement is built to leave something behind for the next one patterns, infrastructure, governance that already held up in production  so the second engagement doesn’t start from zero, and the tenth looks nothing like the first.

Requirements

• Proven experience taking AI systems from prototype to production inside a real operating environment, not just in a lab or sandbox.
• You treat LLM/RAG architectures, agentic systems, cloud platforms, and data pipelines as tools for redesigning how work gets done, not as the deliverable — and you’re strong and current enough with all of them to actually use them that way.
• Comfort mapping decision logic that’s partly undocumented, and judgment about where automation should stop and human accountability should start.

• Excellent communication and stakeholder management — able to advise a client directly and escalate without being asked.

   

  Responsibilities

   

• Embed directly with the client’s operational team to find the workflow that’s actually costing them time, quality, or money before recommending any tooling.
• Own the redesign end to end: rework the decision flow and handoffs around AI, then take the resulting system into production yourself.
• Translate a vague, cross-functional business problem into a concrete technical plan the client’s team can actually execute against.
• Prototype fast enough to show the client what’s possible, then build only the parts of that prototype the redesigned workflow actually needs.
• Where the redesign calls for it, build the agentic systems, RAG pipelines, or custom data pipelines that make it real never a deliverable in itself, always because the workflow needs it running in production.
• Manage stakeholder alignment across the client’s org, escalating early and requesting support before a blocker becomes a delay.
• Build up the client’s own team alongside the system pair with their people, explain the reasoning behind each decision, and leave them able to run and improve what you built after you’ve moved to the next engagement.
• Build the feedback loop from day one  telemetry, evaluation pipelines, human-in-the-loop review — so the system keeps improving after you’ve moved on.

We’re looking for an Applied AI Engineer (Squad Lead) to build production-grade AI agents and applications for an international fintech company operating across multiple markets.

This is a hands-on role where you’ll turn real business challenges into AI-powered solutions — from idea and POC to production and continuous improvement. You’ll work directly with business stakeholders, use AI-native development tools daily, and help shape the team as it grows.
 

What you’ll do:

• Build and deploy AI agents using LLMs, RAG, tool calling, memory, and multi-agent orchestration.
• Develop end-to-end applications, APIs, and integrations with internal systems.
• Design AI pipelines for data ingestion, embeddings, and retrieval.
• Own production systems, from architecture and deployment to monitoring and optimization.
• Collaborate with business stakeholders and mentor engineers while staying hands-on.

What we’re looking for:

• 7+ years of software engineering experience in backend or full-stack development.
• Experience leading engineers or owning a technical domain.
• Proven experience deploying AI agents and LLM-powered systems to production.
• Daily use of AI-native development tools such as Cursor or Claude Code.
• Strong system design, cloud architecture, and frontend/backend skills.
• Experience with vector databases, embeddings, and AI orchestration.
• Fluent English and strong communication skills.

Nice to have: LangGraph, LangChain, LangSmith, experience with regulated environments, and AI evaluation frameworks.

If you enjoy building AI systems that solve real business problems and make it to production, let’s talk!

The project. A UK startup founded by experienced founders with successful startups behind them, now closing its funding round. Their AI agents interview a company's employees about how they work, map the organisation's processes, and then build and run agents that automate them. That includes the infrastructure, integrations with Slack and Teams, and dashboards showing hours saved and the return on AI.
 

The team. It's small and very advanced in AI-driven development (about 100 PRs a week with agents). It has a senior CTO and a fast junior engineer, and needs a strong senior engineer in between.
 

What you'll do. This is a hands-on role, not management. You'll own the quality of the LLM product (evals, prompts, conversation quality, guardrails), improve the AI dev process, and design parts of the system (RAG, memory, agent security).
 

Must-haves:

• You've shipped production LLM products, ideally conversational or agentic
• Hands-on experience with evals
• Strong system design for LLM systems
• Fluent in agentic development
• Good English

• Full focus on this project

   

Nice to have:

• Microsoft Teams / SharePoint / Graph API integrations
• Voice agents
• Knowledge graphs
• Experience with GDPR, SOC 2 or the EU AI Act
• Early-stage startup experience
   

We offer:

• 15 paid day-offs per year.
• 10 UK/UA holidays.
• Flexible schedule and fully remote work from anywhere with reliable overlap.
• Minimal bureaucracy, high authonomy and trust, fast decisions.
   

Approaching stages:
1. Two-way Q&A with me.
2. Meet & Greet with their СТО.
3. Meet & Greet with their Team.
4. ...
5. PROFIT

Meet the YozmaTech

YozmaTech isn’t just another tech company – we’re a global team of go-getters, innovators, and A-players helping startups and product companies scale smarter and faster.
We build dedicated development teams across 10+ countries, creating strong, long-term partnerships based on trust, transparency, and real impact.
Here, every idea counts. We value people who are proactive, open-minded, and ready to grow. If you’re passionate about building meaningful products and want to join a team that feels like family – you’ll feel right at home with us.

We are looking for someone who:

🔹Uses advanced AI coding tools and agents as an integral part of the software development lifecycle.
🔹Knows how to use AI effectively for coding, debugging, testing, code exploration, refactoring, documentation, and technical research.
🔹Can design effective workflows around AI rather than relying on simple prompting.
🔹Can identify engineering tasks and processes that can be automated or significantly accelerated with AI.
🔹Understands both the capabilities and limitations of AI-generated code and applies strong engineering judgment when reviewing and deploying it.
🔹Bonus: has built internal AI tools, agents, automation workflows, or AI-powered product capabilities.
 

Key Requirements:

🔹 5+ years of professional software development experience, primarily in backend development;
🔹 Strong experience designing and building production-grade services and APIs;
🔹 Strong software engineering fundamentals, including system design, data structures, clean code, and scalable architecture;
🔹 Strong experience working with C# / .NET ;
🔹 Strong experience with SQL and relational databases, preferably MySQL;
🔹 Experience working with AWS or other cloud platforms;
🔹 Experience with distributed systems, high-scale environments, and production troubleshooting;
🔹 Experience integrating with complex external APIs and third-party platforms;
🔹 Strong ownership mindset — comfortable taking a problem from initial definition through production;
🔹 Strong communication and collaboration skills;
🔹 Ability to independently explore unfamiliar domains and technologies and quickly turn them into working solutions;
🔹 English – Upper-Intermediate or higher.

What you will do:

🔹Design, develop, and own scalable backend services and APIs supporting our social advertising capabilities;
🔹 Build and maintain integrations with leading social platforms such as Meta, TikTok, YouTube, and other advertising ecosystems;
🔹 Take end-to-end ownership of features — from technical design and implementation through production rollout, monitoring, and optimization;
🔹 Work with complex third-party APIs, authentication flows, data models, platform limitations, and constantly evolving external integrations;
🔹 Build reliable, high-scale distributed services operating in a cloud production environment;
🔹 Develop a deep understanding of the product and business use cases, and contribute to product and technical decisions — not only implementation;
🔹 Identify opportunities to simplify systems, automate processes, and improve engineering velocity;


Interview stages:
🔹 HR Interview YozmaTech;
🔹 Technical Interview;
🔹 Live Coding Session;
🔹 Interview with CTO;
🔹 HR Interview;
🔹 Reference Check;
🔹 Offer.

 

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

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.

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.

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.
   

Experience: 6+ years
Project Duration: November 1, 2026 – November 30, 2027
Location: Remote from Poland

About the Project

We are looking for an AI Agent Developer to design, build, test, and deploy production AI agents using Microsoft technologies. The role combines hands-on agent development with architecture, security, governance, integration, and stakeholder collaboration.

Responsibilities

• Build, test, and deploy production AI agents using Copilot Studio.
• Develop agents within the Azure AI Foundry ecosystem.
• Design agent architectures and apply appropriate design patterns.
• Develop reliable prompts and select suitable tools and connectors.
• Integrate AI agents with the systems required for specific use cases.
• Perform functional, security, and compliance testing of AI agents.
• Work across development, test, and production environments and follow appropriate release practices.
• Assess business use cases and determine whether an AI agent is a suitable solution.
• Analyze agent failures and identify the reasons for incorrect behavior.
• Identify reusable approaches and contribute to a library of design patterns.
• Work closely with business owners and support handover and knowledge transfer.
• Maintain clear documentation and ensure operational readiness.
• Consider long-term maintainability, platform evolution, and future replacement of solutions.
• Build solutions within established security, governance, and compliance frameworks.

Requirements

• 6+ years of professional experience.
• Hands-on experience with Copilot Studio.
• Experience with Azure AI Foundry.
• Strong understanding of AI agent architecture and design patterns.
• Strong prompt engineering skills.
• Understanding of connectors, permissions, and knowledge-source governance.
• Experience testing AI agents, including security and compliance testing.
• Understanding of DLP, prompt injection risks, and access control.
• Experience working across development, testing, and production environments.
• Experience integrating AI agents with external systems.
• Strong analytical skills, including use-case evaluation and failure analysis.
• Ability to identify and develop reusable solutions.
• Experience working within governance and security frameworks.
• Strong stakeholder management and business-facing communication skills.
• Good documentation and knowledge-transfer skills.
• Understanding of operational readiness and support models.
• Awareness of long-term maintainability and platform evolution.

Tech Stack

• Copilot Studio
• Microsoft Azure
• Azure AI Foundry
• AI Agent Architecture
• Design Patterns
• Prompt Engineering
• Integrations
• Security & Compliance