Jobs ML / AI

Brief introduction
You will build production RAG and LLM systems that read real documents and run inside enterprise ERP and finance stacks.

This is a solo, end-to-end role. You join client calls, design the architecture, then build the important parts yourself. Our core stack is Python, Django, Angular and RAG. Ukraine/EU hours.

About us

Deploy Staff automates the manual work large enterprises run on: finance, operations, customer service, reporting. We build complex systems for clients in the US and UAE (currently primarily UAE), centered on production RAG and LLM workflows that read real documents and integrate with real ERP and finance systems.

Despite the name, we don't place engineers into other people's teams. We are not an outstaff company. We own the solutions we build end to end, and so will you.

The role

Solo and end to end. You are the engineer on your projects: there is no development team, and the technical work is yours from discovery through production support.

You sit in on client calls with the project manager, understand the business problem, design the architecture, then open the codebase and build it yourself. The PM runs the relationship and the commercial side. You own the system.

Solo does not mean isolated. You have direct access to the people making decisions, and we talk architecture through with you before you commit to it. After that the code is yours to write and merge. Part of the job is judgement about which calls are yours and which should come back to us, and we would rather be asked than surprised.

If you have spent recent years distributing work and reviewing it, this will feel like a step backwards. If you have spent them wishing there were fewer people between you and the problem, it will not.

What we expect

Our core stack is Python, Django, Angular and RAG/LLM-based workflows. That is what we need you to already be good at.

Core

• Production LLM work: RAG (retrieval design, chunking, evaluation), document processing, structured extraction or agentic workflows. Shipped and operated by you, through the parts that only show up after real users arrive
• Strong Python with Django or DRF, and PostgreSQL data models you can design and debug in production
• Angular and TypeScript. You own the frontend of what you build, so you need to be able to ship a feature through it without waiting for anyone
• Advanced English (C1). You will question senior stakeholders directly and explain a decision a second way when the first one does not land

Also part of the work

You will hit all of this. We do not expect equal depth in every line, and we do expect you to pick up what you are missing.

• Celery, Redis, queues and asynchronous processing
• Enterprise integration: ERP, finance, CRM systems and their APIs
• Cloud infrastructure, deployment, observability and security. AWS, GCP, Kubernetes, Docker
• Reading an existing system before changing it, and keeping what already works

What matters more than the CV

What you personally built, what you personally decided, and what happened when it broke. If your strongest examples are systems your team implemented while you supervised, this is not the right fit.

How we work

Remote, with working hours aligned to the Ukraine time zone.
Small team, direct access to decision makers, real operational problems. You get problems to solve rather than specs to implement.

Interview

1. Introductory interview.

2. Technical interview with us.

3. Test task.

4. Offer.
Interviews are recorded and shared only within the hiring team, so decisions are made on what you actually said rather than someone's notes.

Repeating once again - our core stack is Python, Django, Angular and RAG! We cannot compromise on any of these. If one of those isn't present or barely used - this is an immediate mismatch!

Are you passionate about building production-grade AI systems that continuously learn and improve from real-world feedback? We are looking for a Senior ML Engineer / Data Scientist to help develop intelligent recognition and entity-matching solutions for a large-scale media data platform.

In this fully remote role across Europe, you will work with Large Language Models, evaluation frameworks, and cloud-based ML pipelines to improve automation quality and reduce manual processing efforts. You will collaborate closely with Data Engineering teams and Customer stakeholders while owning the ML lifecycle end-to-end.

We at Sigma Software create impactful technology solutions for global customers and provide engineers with opportunities to work on meaningful, high-scale products using modern AI technologies. This role offers significant ownership, challenging engineering tasks, and the ability to influence production AI systems at scale.
 

Customer

Our Customer operates a large-scale platform focused on processing and structuring advertising and media operational data. The company is actively investing in intelligent automation and machine learning solutions to improve recognition accuracy across multiple station and network layouts while minimizing manual intervention in data processing workflows.
 

Project

The project focuses on building a self-learning Postlog and Prelog recognition system capable of automatically understanding new layouts, extracting structured data, and improving from production feedback. The solution leverages Large Language Models and modern ML practices to optimize recognition quality, entity matching, and confidence-based automation.

You will contribute to the development of scalable AI-driven workflows designed to achieve high automation accuracy, observability, and operational efficiency in production environments.

Responsibilities

• Design and develop a self-learning Postlog and Prelog recognition system using modern ML and LLM techniques
• Build and maintain versioned prompts, evaluation datasets, and few-shot exemplars
• Apply production-grade LLM practices including schema-constrained extraction, grounding strategies, and low-confidence fallback handling
• Improve recognition quality and optimize layout and header mapping performance
• Analyze production failures and enhance prompts, retrieval pipelines, and model behavior
• Run evaluation pipelines and shadow-mode comparisons against legacy systems and gold datasets
• Monitor confidence scores, latency, operational quality, and infrastructure costs
• Develop entity-matching systems for Station, Advertiser, and CreativeID master data
• Implement confidence scoring, thresholding, and auditability mechanisms
• Transform human and machine corrections into labeled signals for continuous model improvement
• Monitor prompt and model drift in production environments
• Collaborate with Data Engineering teams on ML integration and operationalization
• Communicate technical findings and recommendations to engineering teams and Customer stakeholders

Requirements

• At least 5 years of experience in Machine Learning, Data Science, or ML Engineering
• Proven experience delivering ML models or LLM-powered systems into production
• Strong hands-on experience with Large Language Models in real products or pipelines
• Deep understanding of prompt engineering, prompt versioning, evaluation methodologies, and grounding strategies
• Experience handling low-confidence scenarios and optimizing cost and latency for LLM systems
• Strong Python and SQL skills
• Solid knowledge of statistics, confidence estimation, sampling, hypothesis testing, and threshold optimization
• Experience with classification, ranking, matching, or recommendation-related problems
• Understanding of offline evaluation metrics, holdout validation, and production monitoring
• Hands-on experience with AWS cloud services including S3, IAM, CloudWatch, and orchestration services
• Strong communication and collaboration skills
• Upper-Intermediate English level or higher
   

Will be a plus

• LLM-related certifications
• Experience with Amazon Bedrock or equivalent enterprise LLM platforms
• Production experience with Claude/Sonnet-class models
• Experience with Excel or layout extraction systems
• Knowledge of confidence calibration, active learning, or weak supervision techniques
• Experience with cost-aware LLM operations including caching, routing, and fallback models
• Advertising or media domain knowledge
• Familiarity with Glue, Airflow, or similar orchestration and data pipeline tools

Ми шукаємо Senior Software Engineer, який долучиться до розвитку платформи для AI Agents нідерландської технологічної компанії та працюватиме на перетині AI Agents, Full-stack Development і Cloud Infrastructure.

Ви будете розробляти production-рішення end-to-end від технічної специфікації та архітектури до реалізації, тестування й deployment.

Що важливо:

- 5+ років комерційного досвіду у software engineering.
- Сильний Python або TypeScript / Next.js та готовність працювати з обома напрямами.
- Досвід розробки API, PostgreSQL, data models, migrations та access control.
- Досвід роботи з cloud production systems, containers, CI/CD та configuration management.
- Здатність працювати з існуючим mature codebase / monorepo.
- LangGraph, LangChain або інший agent framework у production.
- Досвід роботи з LLM-powered продуктами.
- Upper-Intermediate англійська для щоденної письмової та усної комунікації.

Буде плюсом:

- GCP, Terraform.
- Next.js App Router, Prisma, Auth0 / NextAuth.
- Gemini / Vertex AI, Langfuse / LangSmith.
- Досвід із PDF/document processing, OCR або table extraction.

Що потрібно робити:
 

- Розробляти та покращувати AI agent workflows на базі LangGraph / LangChain.
- Працювати з LLM, structured outputs, validation та AI extraction pipelines.
- Розвивати web-продукт на Next.js / React / TypeScript.
- Працювати з Python, API, PostgreSQL, Prisma.
- Розгортати та підтримувати production-системи в GCP.
- Працювати з Terraform, Docker, GitHub Actions, CI/CD.
- Дбати про якість, тестування, observability та надійність production-систем.

Ми пропонуємо:

- Remote work
- Конкурентну заробітну плату
- Роботу над реальним AI-powered продуктом у міжнародній команді.
- Високий рівень технічної автономності та ownership.
 

PwC is a global network of more than 370,000 professionals in 149 countries that turns challenges into opportunities. We create innovative solutions in audit, consulting, tax and technology, combining knowledge from all over the world.

We are looking for a Junior AI Developer to join our CEE IT Digital Solutions team and help build innovative AI solutions for business users.

You will work closely with experienced developers, business analysts, project managers, security teams, and other stakeholders to support the design, development, testing, and maintenance of AI-powered solutions built primarily on Microsoft Copilot Studio, Power Platform, and the Azure ecosystem.

This role is ideal for someone who is passionate about AI technologies, enjoys learning new tools, and wants to grow their skills in enterprise AI development. You will have the opportunity to work on AI agents, automation solutions, and modern AI technologies while being supported by experienced team members. 

What You’ll Do:

• Assist in building, testing, deploying, and supporting AI-based solutions using Microsoft Copilot Studio, Power Platform, Azure, and related technologies. 
• Configure and maintain AI agents, workflows, topics, prompts, and integrations. 
• Support the development of AI-powered business applications, prototypes, and proof-of-concept solutions. 
• Work with enterprise knowledge sources to improve AI agent responses and user experience. 
• Create and maintain integrations with Microsoft services, APIs, and business applications. 
• Participate in solution testing, troubleshooting, issue resolution, and continuous improvement activities. 
• Contribute to technical documentation, user guides, and knowledge-sharing materials. 
• Learn and apply AI best practices, governance requirements, and security standards. 
• Collaborate with team members and stakeholders to understand business requirements and translate them into practical AI solutions. 

What We Need From You:

• 1–2 years of experience in software development, application support, automation, Power Platform, or a related technology role.
• Interest in Artificial Intelligence, Generative AI, intelligent automation, and modern digital technologies.
• Interest in building AI agents and workflow-based solutions.
• Basic Python skills (e.g., variables, functions, algorithms).
• Basic hands-on experience with Microsoft Copilot Studio, Power Platform, or similar low-code development platforms.
• Familiarity with Power Automate workflows and business process automation.
• Basic understanding of AI agents, prompts, and Generative AI concepts.
• Understanding APIs and application integrations.
• Understanding of Generative AI concepts such as RAG, vector search, and knowledge grounding.
• Basic knowledge of Azure services and cloud technologies.
• Familiarity with data sources such as SharePoint, Dataverse, SQL, or other business systems.
• Basic knowledge of GitHub or version control concepts.
• Strong problem-solving and analytical skills.
• Willingness to learn new technologies and continuously develop technical skills.
• Good communication skills and ability to work in a collaborative environment.
• Upper-intermediate English proficiency.

What Is Nice To have:

• Microsoft Foundry exposure.
• Familiarity with Azure services such as App Services, Functions, Storage, or Azure SQL.
• Awareness of agentic AI frameworks such as LangChain, LangGraph, AutoGen, or Microsoft Agent Framework.
• Microsoft Graph API knowledge.
• Azure DevOps, CI/CD, or GitHub workflows.
• Experience with Power BI, Microsoft Fabric, or other analytics platforms. 

Policy statements:
https://www.pwc.com/ua/uk/about/privacy.html

PwC is a global network of more than 370,000 professionals in 149 countries that turns challenges into opportunities. We create innovative solutions in audit, consulting, tax and technology, combining knowledge from all over the world.

We are looking for a Senior AI Developer to join our CEE IT Digital Solutions team and build high-quality enterprise AI solutions.

You will work closely with other developers, business analysts, project managers, security teams, and other stakeholders to design, develop, deploy, and support AI-based solutions built primarily on the Microsoft Power Platform and Azure ecosystem.

This role is ideal for a hands-on developer with strong experience in Microsoft Copilot Studio, Microsoft Foundry, AI agents, Azure services, and modern AI engineering frameworks. The developer should be able to quickly prototype, deliver MVPs, and build production-ready solutions. Continuously improving AI solutions while applying strong engineering, security, and delivery practices is required. 

What You’ll Do:

• Build, test, deploy, and support AI-based solutions using Microsoft Copilot Studio, Microsoft Foundry, Azure and related technologies. 
• Design and implement AI agents, workflows, orchestration patterns, integrations, and Human-in-the-Loop solutions. 
• Develop AI-powered applications, APIs, services, prototypes, MVPs, and production-ready solutions. 
• Implement RAG, knowledge grounding, embeddings, chunking, and vector search approaches to improve AI solution quality and relevance. 
• Build integrations with other enterprise systems, Microsoft services, databases, APIs, and cloud services. 
• Develop solutions using Azure services such as App Services, Functions, Blob Storage, Key Vault, Azure SQL, and other Azure platform services. 
• Optimize prompt engineering strategies, model selection, evaluation, monitoring, observability, and continuous improvement of AI solutions. 
• Troubleshoot, debug, optimize, and maintain AI solutions across development, testing, and production environments. 
• Create reusable assets, templates, write technical documentation, and engineering best practices. 
• Support members to grow AI engineering capabilities across the team. 

What We’re Looking For:

• 5+ years of experience in software engineering, application development, or intelligent automation development. 
• 2+ years of experience designing and delivering AI, GenAI, intelligent automation, or machine learning solutions. 
• Advanced hands-on experience with Microsoft Copilot Studio - agents, workflows, evaluation, orchestration, integrations, skills, topics etc. 
• Strong hands-on experience with Microsoft Foundry including custom agent hosting on Foundry. 
• Strong experience with Azure OpenAI and Azure AI Search. 
• Proficient Python development skills. 
• Basic knowledge of Streamlit for building AI applications, demos, internal tools, or prototypes. 
• Strong understanding of REST APIs and hands-on experience with API development frameworks and tools such as Spring Boot, FastAPI, Express.js or similar technologies. 
• Practical experience with Azure clous services such as App Services, Azure Functions, Blob Storage, Key Vault, Azure SQL, storage, integration, and other Azure platform services. 
• Hands-on experience with SQL and relational databases for application development, data analysis, and troubleshooting. 
• GitHub and source control knowledge. 
• Prompt Engineering skills. 
• MCP - Model Context Protocol applied knowledge. 
• Be familiar with LangChain and/or LangGraph 
• Strong understanding of AI-assisted software development practices, including the effective use of tools such as M365 Copilot, Cursor AI, Claude Code, and similar AI-powered engineering assistants. 
• Solid knowledge of embeddings, chunking strategies, vector search architectures, and RAG implementations. 
• Experience implementing agentic workflows, orchestration patterns, multi-agent solutions, and Human-in-the-Loop AI workflows. 
• Experience with LLM evaluation techniques, AI quality metrics, benchmarking approaches, and solution evaluation methodologies. 
• AI observability, tracing, and monitoring concepts. 
• AI cost optimization and token consumption awareness. 
• Ability to write clean, modular, maintainable, and well-documented code. 
• Ability to communicate effectively with both technical and business audiences. 
• Fluent spoken and written English. 

What Is Nice to Have:

• Power Platform - Power Automate. 
• Azure DevOps CI/CD. 
• Microsoft Graph API. 
• Agentic frameworks: Microsoft Agent Framework, AutoGen, CrewAI, and other modern agentic frameworks. 
• Vector Databases knowledge: Qdrant, ChromaDB. 
• Data & Analytics Platforms: Databricks, Microsoft Fabric. 
• Containers, Docker, Kubernetes. 
• Voice agents and conversational AI solutions, including platforms such as ElevenLabs or similar providers. 

Policy statements:
https://www.pwc.com/ua/uk/about/privacy.html

This is a fantastic opportunity to join a fast-growing company at the heart of the digital revolution. Our software product is revolutionising manufacturing through automation. We are trusted by global brands and work across sectors (mobility, consumer goods, machinery etc).

We have a talented and ambitious team. We value integrity and are passionate about our mission to revolutionise advanced manufacturing.

This is your opportunity to:

• Be part of an AI product company in advanced manufacturing.
• Be part of a research focused team.

Responsibilities: 

• Research, test and develop generative AI based solutions.
• Collaborate with mechanical engineers to enhance your research.
• Design and implement end-to-end AI solutions that integrate with existing systems.
• Collaborate with software engineers and product teams to understand business needs and translate them into technical solutions. 
• Research emerging AI trends and techniques to continually improve the AI solution offerings. 
• Prepare and maintain documentation on design, code, and processes to ensure organizational knowledge retention. 
• Monitor and evaluate the performance of AI systems in production, identifying areas for improvement or further development.

You will be joining a well-versed team if you have:

• Bachelor’s or Master’s degree in Computer Science, Engineering, Mathematics, or a related field. 
• Proven experience in developing generative AI or machine learning models.
• Commercial experience in using large language models.
• Programming skills in languages such as Python or JavaScript.
• Familiarity with databases (SQL, NoSQL). 
• Solid understanding of deep learning, NLP, computer vision, or other specialized areas within AI is a plus. 
• Excellent problem-solving skills and the ability to work in a fast-paced, collaborative environment.
• Good communication skills and the ability to translate complex technical concepts to non-technical stakeholders. 
• Commitment to continuous learning and development in the field of AI and emerging technologies.

We're a Registered Anthropic Partner and an Official Advanced Tier AWS Partner, currently serving 100+ enterprises and startups across the US, EU, and other Tier 1 markets.
 

We're starting a new product, Tokensaver: unified access to AI models for companies that use AI heavily, with the explicit goal of cutting their AI bill. You'd be the first engineer on it, building from scratch. 

We are looking for a Founding AI Engineer who will build the "Tokensaver" product from scratch.

AI Router technology. This is the core of the product, so it should be the part you're most curious about. We expect candidate to have genuine interest in AI Router technology: model selection, routing logic, caching, fallbacks, and the cost/quality tradeoffs behind each. 

What we expect:

• 3+ years of practical software engineering experience
• You build with AI agents daily and use latest AI coding approaches in your daily workflow
• Tech stack: Node.js, TypeScript, Next.js, PostgreSQL, ClickHouse, basic knowledge of Go or Rust is a plus
• Hands-on experience with LLM APIs, agentic workflows, RAG, embeddings, structured outputs, prompt design, and where models break down
• Experience building or integrating MCP servers, APIs, connectors, and components
• Product-oriented thinking, understanding what to build - product judgment about what to ship and what to deliberately leave out
• Genuine interest in AI Router technology

What we offer and why it's great opportunity:

• Founding ownership. You're the founding engineering hire for Tokensaver product - you choose the architecture, the stack and decision on how to build. 
• Competetive base salary & equity compensation from day 1.
• Clear career growth. There is a clear path to becoming the technical leader of Tokensaver product and building the engineering team around you.
• Work on technology that is just being invented right now. AI routing and multi-model infrastructure are still at a very early stage, with best practices being defined in real time. You’ll work on intelligent model selection, caching, fallbacks, observability, and cost/quality/latency optimization at the frontier of modern AI infrastructure.
• Distribution & real Credibility behind the company from day one. We're a Registered Anthropic Partner and an Official Advanced Tier AWS Partner. Our existing business already serves 100+ companies across the US, Europe, and other Tier 1 markets, giving Tokensaver a strong base for early users, feedback, and distribution.

To apply, please answer 2 questions:

1) How do you use AI tools in your daily work? Be specific - which AI tools, for which parts of the job. 

2) Our goal is to build an AI Router Technology - unified access to AI models that cuts costs for businesses already spending heavily on AI. How would you approach building this from scratch?

We are looking for a Senior MLOps Engineer to join Sigma Software and help build a production-grade ML platform for a large-scale AdTech ecosystem. You will work on infrastructure powering predictive decision-making systems that process hundreds of millions of auction requests daily.

As part of a dedicated engineering team, you will contribute to scalable ML orchestration, model lifecycle automation, observability, and real-time optimization workflows. This role is ideal for engineers with strong production experience who enjoy solving complex platform and operational challenges.

We at Sigma Software offer the opportunity to work on cutting-edge ML infrastructure projects, collaborate with experienced engineers, and influence architecture decisions in a long-term strategic engagement.

CUSTOMER

Our Customer is a technology company operating supply-side infrastructure within the programmatic advertising ecosystem. The company manages a high-load ad exchange platform handling hundreds of millions of auction requests every day and is investing in advanced predictive decision-making capabilities to improve advertiser outcomes and real-time optimization processes.

PROJECT

Sigma Software is building a predictive modeling and optimization platform integrated with a live ad exchange environment. The solution enables real-time supply scoring and filtering, audience look-alike generation, contextual performance estimation, and multi-objective optimization under operational constraints.

The project combines large-scale ML infrastructure, automated model lifecycle management, multi-tenant architecture, and advanced observability practices. The team focuses on delivering reliable, reproducible, and scalable ML systems ready for long-term Customer ownership.

Key Technologies: Python, Kubernetes, Docker, GCP, Vertex AI, MLflow, Airflow, Kubeflow, Argo Workflows, Terraform

Job Description

• Build and maintain ML training orchestration pipelines across hourly, daily, and weekly schedules
• Implement retries, backfills, and idempotent execution mechanisms
• Design and support model registry workflows including versioning, lineage, evaluation gates, and promotion processes
• Develop isolated per-advertiser model environments with namespace and configuration separation
• Build scalable refresh pipelines and publishing workflows for serving infrastructure
• Implement shadow mode and champion/challenger deployment strategies
• Develop monitoring and alerting for ML-specific metrics including feature drift, prediction drift, train/serve skew, and calibration decay
• Ensure reproducibility of ML workflows using containerized environments, pinned dependencies, and data snapshots
• Monitor training and scoring costs across tenants
• Collaborate with DevOps and SRE engineers on CI/CD and infrastructure automation
• Prepare operational documentation and platform handover materials

Qualifications

• 5+ years of experience in MLOps, ML platform engineering, or infrastructure engineering supporting production ML systems
• Strong Python skills and experience building platform-level tooling and automation
• Hands-on experience with Kubernetes and Docker
• Experience building CI/CD pipelines for ML workloads
• Hands-on production experience with MLflow, Kubeflow, Airflow, Argo Workflows, Vertex Pipelines, or similar orchestration and ML lifecycle platforms
• Experience with ML platforms and model lifecycle tools such as Vertex AI, MLflow, or Kubeflow
• Strong understanding of ML observability including drift detection, train/serve skew monitoring, and incident response
• Experience designing or supporting multi-tenant ML systems and isolated model environments
• Experience working with cloud platforms, preferably GCP
• Experience with infrastructure-as-code tools such as Terraform
• Experience with Linux environments
• Understanding of the ML lifecycle and productionization processes
• Upper-Intermediate English level or higher

WILL BE A PLUS

• Experience with feature stores and feature consistency management
• Experience with large-scale batch scoring systems operating under freshness SLAs
• Familiarity with experiment tracking platforms and evaluation gates
• Experience with on-premises Kubernetes or bare-metal Linux infrastructure
• Knowledge of DVC, lakeFS, or other data versioning tools
• Experience with Bigtable, Redis, Aerospike, or similar low-latency serving databases
• GPU scheduling and training cost optimization experience
• Familiarity with SOC 2, ISO 27001, or GDPR-related compliance requirements

PERSONAL PROFILE

• Strong ownership mindset and focus on operational reliability
• Ability to work independently in complex distributed systems environments
• Strong collaboration and communication skills
• Analytical thinking with attention to scalability and maintainability
• Comfortable working in fast-paced product-oriented environments

Backend Software Engineer (Python, AI)
 

Requirements:
- 6+ years of experience in backend design and development of production-grade applications.
- Strong experience with Python
- Solid experience with databases, preferably SQL
- Experience working with large-scale systems
- Experience with AI orchestration frameworks such as LangChain or LlamaIndex, or experience integrating third-party AI APIs such as OpenAI or Anthropic.
- Knowledge of networking infrastructure.
- Cybersecurity experience - a strong advantage.
- Ability to learn quickly and adapt to new technologies.
- Strong teamwork and collaboration skills.
 

Responsibilities:
- Take full ownership of features, from product design through deployment, including end-to-end feature architecture.
- Plan, design, and develop systems with complex performance and scalability requirements.
- Design, maintain, and contribute to the company’s code infrastructure.
- Design, build, and maintain robust, scalable server-side architecture.
- Integrate with Large Language Models (LLMs) and vector

B2B, remote, US Eastern Time clients, 2 calls per week with the team.

About the Role

We are looking for a Senior Forward Deployed Engineer who combines strong hands-on engineering, enterprise infrastructure expertise, and executive presence.

You will work directly with US-based mid-market and enterprise clients, understand complex business problems, design the technical solution, build and deploy it, integrate it into existing enterprise environments, and remain the trusted technical point of contact.

This is not a ticket-based engineering role. You will own the full journey:

Business Problem → Architecture → Build → Integration → Deployment → Client Outcome
 

What You'll Do

• Own client projects end-to-end with minimal handholding
• Turn ambiguous business problems into technical solutions
• Design and build production AI agents, applications, automations, integrations, and data pipelines
• Work with complex enterprise infrastructure, ERP systems, data warehouses, APIs, and cloud environments
• Make architecture and infrastructure decisions independently
• Use AI coding tools to build and ship quickly
• Work directly with client IT teams and senior stakeholders
• Lead client meetings and clearly explain technical decisions, progress, risks, and next steps
   

What We're Looking For

Strong Engineering & Architecture

• Approximately 7–12+ years of software engineering experience; flexible for exceptional candidates
• Strong hands-on development experience with TypeScript/JavaScript and Python
• Experience with technologies such as Next.js, PostgreSQL, Supabase, and APIs
• Ability to independently design system architecture and ship production software
• Former CTOs, Tech Leads, architects, founders, and consultants are welcome if they are still hands-on
   

Enterprise Infrastructure

Strong enterprise infrastructure experience is a key requirement.

You should have experience with:

• AWS, Azure and/or GCP
• ERP systems and enterprise integrations
• Data warehouses and data pipelines
• Microsoft/enterprise environments
• Authentication, security, and APIs
• Complex or legacy enterprise systems

You should be able to confidently discuss architecture and infrastructure with a client's IT team. This was explicitly highlighted by the hiring manager as increasingly important.
 

AI-Native Engineering

You should already use tools such as Claude Code, Codex, Cursor, or similar agentic coding tools as part of your normal development workflow.

Production experience with several of the following is expected:

LLM APIs · AI Agents · RAG · Vector Databases · MCP · Agent Frameworks · AI Automations

We care especially about how you work with AI—context, documentation, agents/sub-agents, code review, testing, and QA.

Executive Presence

This is a highly client-facing position.
 

You must have:

• Excellent spoken and written English
• Strong confidence and executive presence
• Experience communicating with senior client stakeholders
• Ability to explain complex technical topics in business language
• Confidence leading meetings with executives, operations teams, and enterprise IT
• Ability to become a trusted technical advisor rather than relying on someone else to manage the client relationship

The client specifically wants engineers who can independently represent the technical work in senior stakeholder meetings.
 

You're a Strong Fit If

You are a hands-on senior engineer who thinks like an architect, operates like an owner, and communicates like a consultant.

You don't wait for detailed specifications. You can understand the business problem, decide what should be built, build it, integrate it into a complex enterprise environment, and confidently present the result to the client.

Data Science UA is a service company with strong data science and AI expertise. Our journey began in 2016 with uniting top AI talents and organizing the first Data Science tech conference in Kyiv. Over the past 9 years, we have diligently fostered one of the largest Data Science & AI communities in Europe.

About the client and the role:
We are seeking a Senior/Lead NLP & LLM Expert Consultant (AI System Architect / Consultant) to provide expert assessment and help shape the technical vision for AI-driven projects. The role will focus on evaluating existing and potential AI solutions, developing a Statement of Work (SOW), and potentially continuing to support projects as an AI System Architect / Consultant.

The ideal candidate has a strong track record of successfully designing and implementing production-ready solutions based on NLP, LLM, RAG, AI agents, and modern AI architectures.

Responsibilities:
- Provide expert assessment of AI/ML solutions and technical approaches.
- Design and advise on AI system architectures based on NLP, LLM, RAG, and AI agents.
- Help define technical approaches, architecture, and scope of work for AI projects.
- Develop a Statement of Work (SOW) based on business and technical requirements.
- Advise on the selection and integration of appropriate AI/ML technologies and approaches.
- Potentially participate in further project delivery as an AI System Architect / Consultant.
- Collaborate with technical and business stakeholders to identify optimal AI solutions.

Requirements:
- Senior / Lead-level expertise in AI, Machine Learning, NLP, and LLM technologies.
- Proven experience designing and successfully implementing solutions based on NLP, LLM, and RAG.
- Proven experience designing and successfully implementing AI agent-based solutions.
- Experience working with Large Multimodal Models (LMMs).
- Strong experience developing and implementing solutions using classical Machine Learning / Data Science approaches.
- Strong ability to evaluate AI technologies and translate business needs into practical technical solutions.

Nice-to-Have Skills/Experience:
- Expertise in knowledge bases and knowledge management systems.
- Experience with secure AI architectures and deploying models in isolated environments, including on-premise or private cloud.
- Experience with DevOps / MLOps practices and infrastructure.
- Experience working in an AI architecture, consulting, or technical advisory role.

Work format: Remote / Hybrid (Kyiv)
Engagement: Part-time / Contract
Location: Anywhere
Start: ASAP

Розглядаємо як фултайм (голова + руки), так і парттайм, де руки вам дадуть і від вас тільки голова.
__________

Хелоу, люба спільното \0/

Ми продовжуємо нарощувати команду американського Survey SaaS, що аналізує поведінку юзерів під час digital опитувань. По суті, це платформа, де бізнес може засетапити своє опитування та отримати advanced behavioural analytics від нашої моделі на підставі того, як юзер водив мишою, відповідав на різні питання, тупив та чухався.

Вам сподобається, якщо:
- в вас ідеальний інгліш. Це найважливіший фактор. Треба багато діскутувати на складні теми. Якщо вам здається, що в вас не супер сильний інгліш – го не гаяти часу.
- в вас достатньо терпіння для щоденної роботи із гіперактивним фаундером, в якого багато ідей, іноді протилежних.
- ви вмієте поєднувати грацію науки та експеріменти на колінці (напр.: взяти наукову роботу про кореляцію відповідей із часом на роздуми та придумати як превірити це за нишими даними не за мільйон доларів та часу).

По суті, нам потрібен Scientific Lead, який буду допомагати фаундеру народжувати проект, покриваючи наукову та ML частину самостійно, або за допомогою нашого ML Engineer.

На цьому я дозволю перемкнутись на англійську, бо далі конкретніше.

What you'll do

• Act as the scientific and ML lead next to the founder, turning a stream of ideas (sometimes conflicting ones) into testable hypotheses and priorities
• Design lean experiments: take a research paper (e.g. how thinking time correlates with answer quality) and find a cheap, fast way to test it on our data
• Set tasks for our ML Engineer and review the work, or build it yourself
• Own model quality: evaluation methodology, calibration, segment-level analysis, precision/recall tradeoffs
• Keep work reproducible and audit-ready (experiment tracking, clean notebooks, documented results)
   

What you need

• Deep learning on sequence/time-series data (PyTorch, CNNs built from scratch)
• Tabular ML with gradient boosting (LightGBM / XGBoost)
• Rigorous evaluation: imbalanced classification, threshold tuning, AUC-ROC, calibration, label quality
• Solid experimental design and the ability to turn research into practice
• Experiment tracking (MLflow, W&B or similar)
• Excellent spoken and written English
• The patience and structure to work day to day with a fast-moving, idea-heavy founder
   

Nice to have: behavioral/clickstream analytics, fraud/anomaly detection, survey methodology/psychometric.
 

Stack: Python, PyTorch, LightGBM, MLflow, HDF5, PostgreSQL.
 

Not an LLM/GenAI role: this is classical ML and deep learning on structured behavioral data.

The Team

• Playing Founder
• Project Manager
• ML Engineer
• 2x Fullstack Devs
• Anti-Fraud Automation QA
• DevOps

For fulltime players we offer:

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

Role Overview

We are looking for a Senior AI Engineer to own the Python AI service inside a learning-platform programme and act as the technical voice in front of the client.

About one-third to one-half of the role focuses on LLM and agent engineering. The rest covers backend development, data modelling, architecture, and the DevOps needed to keep everything shipping.

Project Description

The client is a US remote online-learning provider. Their learning-content platform is a .NET application; our team builds the Python AI service that sits alongside it, handling retrieval over the platform's content and, increasingly, agent workflows on top of it. The retrieval and recommendation layer is already delivered; the next phase is LLM engineering and agents, with custom model training a possibility later rather than a certainty.

All models used in the system are open-source and deployed on the client's own infrastructure, so this is a self-hosted inference. Agent work uses frameworks in the Google ADK / LangChain family. The .NET side is being taken over by other developers on the team, but you will still need to read and occasionally change it, which in practice means working through a coding agent in a language you may not write natively.

Two things about the environment are worth saying plainly. Requirements move constantly, so the role includes running the conversations that pin them down — meetings, diagrams, written specifications, and the patience to re-explain. And the infrastructure is branched: pipelines run in GitLab CI/CD, environments are separated, and configuration and keys live in repositories the team does not own, so working DevOps ability is a practical requirement.

Key Responsibilities

• Own the Python AI service end to end — retrieval, LLM orchestration, and the agent workflows built on top of it.
• Design and build agent workflows using a Google ADK.
• Work with open-source models deployed on the client's own infrastructure, including selection, prompting, and performance tuning.
• Own the service's data model, database design, and backend architecture.
• Run requirement sessions directly with client stakeholders and produce the diagrams and written specifications that settle them.
• Own policy-governed, auditable AI pipelines: human-review gating, content lineage, tenant/role policy enforcement. 
• Integrate the AI service with the client's .NET learning-content platform, reading and changing that code where needed.
• Maintain and extend CI/CD pipelines in GitLab across separated development environments.
• Trace configuration, keys and pipeline definitions across repositories the team does not own, and unblock delivery when they break.
• Propose an approach and defend it, rather than waiting for the requirement to arrive fully formed.
• Hand .NET-side work over to the developers taking it on, with documentation they can act on.
• Prepare the service for custom model training and evaluation if that work lands with this team.
• Owning prompt/model versioning and an evaluation harness gating changes.

Required Qualifications

• Senior-level commercial Python experience, with ownership of a production service.
• Ability to read and modify .NET / C# code.
• Hands-on LLM engineering in production — retrieval-augmented generation, context design, prompt and output handling.
• Experience building agent workflows with a framework such as Google ADK, LangChain, or LangGraph.
• Backend and database design experience, including making the architectural calls rather than following them.
• Working DevOps ability — CI/CD pipelines, containers, and multi-environment configuration.
• Willingness and ability to work in a codebase written in a language you do not primarily use.
• Strong client-facing communication: running requirement sessions, producing diagrams, and holding a position under pressure.
• English at a level that supports direct client meetings without an intermediary (at least B2 level).
• Comfort with requirements that change between meetings.

Preferred Qualifications

• Experience with document based db like MongoDB, or similar
• Experience with OpenSearch/vector search. 
• Experience with Kubernetes.
• Experience deploying and operating self-hosted open-source models.
• MLOps experience — training pipelines, fine-tuning, model monitoring and evaluation.
• Experience with learning-management or content-management platforms.
• Experience delivering alongside a partner vendor's team, including a business analyst outside your own organisation.
• Daily working experience with coding agents in a large, unfamiliar codebase.

Our client is looking for a Conversational AI Specialist.

Role Overview:We are looking for a Conversational AI Specialist to train and improve our AI agent, maintain its Knowledge Base, monitor conversation quality, and ensure responses remain accurate and up to date. You will also coordinate with our technical vendor to resolve issues and support testing and monitoring of AI updates.Key Responsibilities:

• Train and continuously improve the AI agent's responses through structured content and configuration;
• Maintain and update Knowledge Base content to keep the AI agent's answers accurate and current;
• Monitor live chat conversations to identify inaccurate or unclear AI responses and flag/fix them;
• Update AI configurations when promotions, bonuses, or policies change;
• Coordinate with our technical vendor to report and track issues, ensuring fixes are tested before going live;
• Support monitoring after updates to confirm the AI agent is working correctly for users.

Required Skills & Experience:

• To be fluent in Polish (native or near-native) and English, both written and spoken;
• Experience with AI chatbot or virtual assistant platforms (e.g., Google Dialogflow, or similar conversational AI tools) is preferred;
• Strong attention to detail and a structured, analytical mindset for identifying and resolving inconsistencies in AI responses;
• Comfortable working with basic structured data formats (e.g., reading simple JSON-like data) — full training will be provided;
• Experience using project management or ticketing tools (e.g., Jira, Trello, Asana, or similar) is a plus;
• Strong written communication skills, with the ability to document issues clearly and coordinate with technical teams.

Will be a plus:

• Prior experience in iGaming, customer support, or live chat operations is a plus;
• Prior experience in content writing, knowledge base management, or FAQ documentation is a plus;
• Curiosity about AI/chatbot technology and willingness to learn new tools.

The company guarantees you the following benefits:

• A positive workplace atmosphere that creates a culture of collaboration and support, making it a place you'll love working in;
• Competitive compensation and regular career development reviews;
• Flexible working hours and remote working options, you'll enjoy the freedom that the company provides;
• A generous vacation and sick leave policy, allowing you to take time off and enjoy a work-life balance;
• Financial assistance for professional development, helping you stay ahead of the curve and love your career path;
• Educational Allowances that give you the opportunity to expand your knowledge and experience;
• You'll have a monthly allowance for personal activities, giving you the opportunity to pursue your interests and hobbies outside of work;
• A comprehensive health insurance plan, depending on your current location;
• Referral program with financial rewards for bringing top talent to the company;
• Engaging in team-building activities and corporate parties.

Interview process:

• HR Interview with the Recruiter;
• A 1-hour technical inetrview;
• A 1-hour final interview with the team;
• Final decision.

If you find this opportunity right for you, don't hesitate to apply or get in touch with us if you have any questions!

Who we are:

Adaptiq is a technology hub specializing in building, scaling, and supporting R&D teams for high-end, fast-growing product companies in a wide range of industries.

About the Product:

We are building and scaling a mature, data-intensive B2B SaaS platform used by enterprise customers across multiple markets. The platform supports a diverse range of enterprise use cases across operational planning, information analysis, case management, and cross-team collaboration.

The product brings together large volumes of structured and unstructured data, domain-specific analytics, and configurable workflows to help users investigate complex cases, collaborate effectively, and make timely operational decisions.

About the Role:

We are looking for a Principal / Staff AI Engineer to design, build, and deliver reliable AI-powered capabilities as part of an established production platform.
You will work at the intersection of backend engineering, generative AI, and product development. Your responsibilities will cover the full delivery cycle – from exploring ideas and validating technical approaches to building production services, evaluating output quality, and improving solutions based on real-world usage.
This is a hands-on engineering role with significant ownership. You will have the opportunity to influence architectural decisions, engineering practices, and the broader adoption of AI across the product while working closely with engineering, product, and other cross-functional teams.

Key Responsibilities:

• Design, build, and deploy production-grade autonomous agent systems that solve open-ended, complex, and multi-step tasks for real users.
• Build the core agent platform and harness, including planning, tool use, agent orchestration, context management, memory, and reusable agent skills.
• Develop agents that can independently determine their next steps, adapt based on intermediate results, and maintain direction during long-running tasks.
• Design human-in-the-loop mechanisms that define when agents can act independently and when human guidance, review, or approval is required.
• Develop methods and tooling to validate AI-generated results, evaluate agent behavior, diagnose failures, monitor production performance, and improve reliability over time.
• Build scalable Python backend services and integrate agent capabilities with distributed production systems, taking new functionality from experimentation to reliable real-world use.
• Own key architectural and technical decisions, establish AI engineering standards, and introduce new approaches that advance the team’s agent platform and engineering expertise.

Required Competence and Skills:

• 7+ years of software engineering experience, including at least 1.5 years of hands-on experience building and shipping LLM-based products to production.
• Proven experience building autonomous AI agent systems used by real users at meaningful scale and capable of handling complex, open-ended, multi-step tasks.
• Hands-on experience with AI agent frameworks such as LangChain, LangGraph, Deep Agents, or similar. Experience selecting frameworks, identifying their limitations, and building custom components where needed.
• Strong backend engineering skills in Python or another language such as Golang, Java, or Rust, with the willingness to work primarily with Python.
• Experience with context and memory management, agent orchestration, and human-in-the-loop systems.
• Experience taking AI products from experimentation to reliable production use, including cloud deployment, system integration, AI quality validation, monitoring, and agent failure analysis.
• Strong end-to-end ownership, communication, and ability to make technical decisions, work independently, and adapt quickly in a high-velocity environment.
• Advanced English skills.

Nice to Have:

• Experience with React.js and full-stack development, with the ability to contribute to frontend development when needed.
• Experience with vector databases and similarity search in production AI applications.