Jobs

Your expertise:

• High personal interest in quantitative and algorithmic approaches
• Knowledge in quantitative analysis, statistics, time-series analysis, ML modeling and forecasting for markets
• Experience from 2 years with Data Science activities, including data research and analysis, algorithmic strategy prototyping and backtesting
• Experience with creating and supporting algorithmic strategies, including their risk management
• Experience in systematically monitoring and evaluating the performance of algorithmic strategies with a set of KPIs

• Experience with SQL, Pandas / NumPy / SciPy, and backtesting frameworks

   

Will definitely be a plus:

• Experience with effectively managing delta-neutral and grid strategies
• Experience in the management of a portfolio of algorithmic strategies
• Experience with data science for Agentic AI and Machine Learning
• Experience in the DeFi, DeFAI, or market-making

• Good knowledge of Finance for markets

   

What’s in it for you?

• Opportunity to deal with top-notch technologies and approaches in a world-leader product company with millions of customers
• Opportunity to make a difference for online privacy, freedom of speech, and net neutrality
• Decent market rate compensation depending on experience and skills
• Developed corporate culture: no micromanagement, culture based on principles of truth, trust, and transparency
• Support of personal and professional development
  • coverage of costs of external trainings, conferences, professional literature
  • support of experienced colleagues
  • in-house events and trainings
  • regular knowledge sharing in teams
  • English classes and speaking clubs
• Life-balance support
  • 25 working days of vacation
  • 5 days of paid sick leave per year without providing a medical certificate (no limitation on sick leaves with medical confirmation)
  • generous maternity / paternity leave program

• Professionally strong environment, friendly and open atmosphere, ability to influence the product development and recognition for it

   

You will be involved into:

• Lead Data Science activities for algorithmic strategies: data research and analysis, prototyping and backtesting, live strategy performance monitoring, designing data pipelines, designing and implementing risk management strategy
• Participate in the full lifecycle of algorithmic strategy development: ideation, data research, strategy design and prototyping, backtesting, implementation, and live monitoring
• Systematically monitor and analyze strategy performance metrics, research and generate hypotheses for improvement, and iteratively test hypotheses

• Define requirements for implementation by Developers of algorithmic strategies and their data pipelines

   

About the company and project:

ZONE3000 is proud to represent its partnership with Namecheap (www.namecheap.com). Namecheap has been on the market for 20+ years and is the 2nd largest domain registry‬ in the world. We are the Namecheap Machine Learning Team.‬

The team prototypes and develops innovative systems with AI and Machine Learning.‬ Currently, there are more than 10 Production systems in the areas of Email, Payments, Customer Service, and Analytics. Some of them have proven quality at the level of global‬ market leaders.‬

The team provides all the conditions for active professional growth. The culture combines‬ the best from enterprises and startups: a high level of professionalism, truly innovative‬ technologies, friendliness, and stability.‬

Our client is an international company developing next-generation AI products that combine large language models, generative AI, and computer vision technologies.

We are looking for an ML Engineer who will help the team build intelligent systems for real-world applications, from text understanding to video analysis.
 

What You’ll Do

• Design and implement ML pipelines in Python using TensorFlow or PyTorch.
• Train, evaluate, and optimize models for performance and scalability.
• Deploy AI solutions to cloud environments (AWS, GCP, or Azure).
• Work on language models (adaptation, fine-tuning, deployment, agent-based architectures).
• Contribute to image/video intelligence projects: motion tracking, pose estimation, action recognition, depth modeling.
• Build backend services to integrate ML models into production systems.

Desired Background
 

• Degree in Computer Science or a related field.
• Strong programming skills in Python.
• 3+ years in applied ML, with exposure to GenAI and Computer Vision.
• Understanding of model lifecycle: training → evaluation → deployment.
• Cloud deployment experience (AWS / GCP / Azure).
• Hands-on with OpenCV, YOLO, or modern vision transformers.

Job Description

We’re looking for a skilled Python Engineer to join our team in building and scaling LLM-powered applications. You’ll be working with modern agentic AI frameworks, designing APIs, and integrating with cloud services – primarily on Azure.

• 4+ years of experience as a Python AI Engineer.
• Strong experience with FastAPI, SQLAlchemy, and PyTest.
• Experience with agentic AI frameworks (e.g., Haystack, LangGraph, CrewAI).
• Familiarity with LLM-based systems and integration patterns.
• Working experience of Docker, Kubernetes, and Git.
• Hands-on experience with Azure cloud services (especially Azure AI, Azure Functions, etc.).
• Familiarity with PostgreSQL.
• Experience with Retrieval-Augmented Generation (RAG), including vector databases and embeddings.
• Experience with Langfuse or similar LLM evaluation/monitoring tools.
• Experience with CI/CD workflows and observability tools.
• Interest in emerging LLM/agentic tooling and frameworks.
• Solid understanding of natural language processing techniques, with experience in deploying NLP systems and working with prompt libraries.
• Expertise in data analysis and analytics.
• Proven track record of driving innovation and solving complex technical problems using AI and machine learning.
• Good communication skills, with the ability to convey complex technical concepts to both technical and non-technical stakeholders.
• Experience working collaboratively within cross-functional teams.
• Understanding of data privacy and security standards, ensuring systems are compliant with industry regulations and best practices.
• Passion for continuous learning and staying updated with the latest trends and advancements in AI/ML technologies.
• Nice to have: Experience with multi-agent architectures.
• Nice to have: Experience with MCP protocol.

Job Responsibilities

• Collaborate with PO, BA, stakeholders to understand the specific needs and requirements of the business process.
• Translate business needs into technical specifications.
• Collaborate with frontend engineers, Data Scientists, and DevOps to deliver scalable LLM solutions.
• Develop and maintain backend services using FastAPI.
• Work with agentic AI frameworks like Haystack to build AI pipelines and components.
• Design and implement robust database models using SQLAlchemy with PostgreSQL.
• Write and maintain unit and integration tests using PyTest.
• Deploy services using Docker and Kubernetes.
• Utilize Azure services (e.g., Azure AI) for hosting, inference, and other cloud-native features.
• Use Langfuse or similar tools for LLM performance monitoring and evaluation and implement improvements as necessary.
• Develop and refine the prompt library to facilitate seamless user interaction and request handling.
• Ensure the AI models integrate effectively with existing applications and workflows.
• Conduct thorough testing of AI models to ensure they meet quality, performance, and accuracy standards.
• Provide ongoing support and troubleshooting to address any system issues.
• Monitor and adapt AI systems to accommodate changes in the business process or user requirements.

• Create comprehensive documentation for developed solutions.

   

Department/Project Description

Global player in the railway sector is looking to create an internal platform aimed to support the Bid and Sales teams during critical stages of the bidding process, as well as to assist to Engineers throughout key phases of the Engineering projects lifecycle.

This solution utilizes various techniques, including multi-agent GenAI, to enhance the requirements and compliance process, facilitate data analysis and tender authoring, provide guidance in engineering, offer technical support, and aid in decision-making. It also generates essential artifacts such as requirements, designs, and tests. Additionally, the solution will enable data analytics to identify trends across bids, supporting the Sales and Product Development teams.

Join us at Provectus to be a part of a team that is dedicated to building cutting-edge technology solutions that have a positive impact on society. Our company specializes in AI and ML technologies, cloud services, and data engineering, and we take pride in our ability to innovate and push the boundaries of what's possible.

As an ML Engineer, you’ll be provided with all opportunities for development and growth.

Let's work together to build a better future for everyone!

 Requirements:

• Comfortable with standard ML algorithms and underlying math.
• Strong hands-on experience with LLMs in production, RAG architecture, and agentic systems
• AWS Bedrock experience strongly preferred
• Practical experience with solving classification and regression tasks in general, feature engineering.
• Practical experience with ML models in production.
• Practical experience with one or more use cases from the following: NLP, LLMs, and Recommendation engines.
• Solid software engineering skills (i.e., ability to produce well-structured modules, not only notebook scripts).
• Python expertise, Docker.
• English level - strong Intermediate.
• Excellent communication and problem-solving skills.

Will be a plus:

• Practical experience with cloud platforms (AWS stack is preferred, e.g. Amazon SageMaker, ECR, EMR, S3, AWS Lambda).
• Practical experience with deep learning models.
• Experience with taxonomies or ontologies.
• Practical experience with machine learning pipelines to orchestrate complicated workflows.
• Practical experience with Spark/Dask, Great Expectations.

Responsibilities:

• Create ML models from scratch or improve existing models. 
• Collaborate with the engineering team, data scientists, and product managers on production models.
• Develop experimentation roadmap. 
• Set up a reproducible experimentation environment and maintain experimentation pipelines.
• Monitor and maintain ML models in production to ensure optimal performance.
• Write clear and comprehensive documentation for ML models, processes, and pipelines.
• Stay updated with the latest developments in ML and AI and propose innovative solutions.

UK Telecommunication Industry Project
Partnership: Global Consulting Enterprise

We are seeking a team of experienced Data & AI Engineers of different skill levels to join a large-scale project for a UK telecommunication client. The role focuses on experimentation — applying business goals to technical requirements and processes of end-user applications.

Whether the challenge is to increase engagement in iPlayer or Sounds, or to improve recommendations in News or Sport apps, experimentation helps us make the right decisions for our users.

Tools & Skills

• Piano Analytics and plug-in Tag Inspector (for tracking in browser)
• SQL IDEs (DataGrip / Workbench / VS Code / AWS Console)
• Optimizely
• GitHub
• Alation or similar (data dictionary)
• Jira and Confluence

Responsibilities

• Collaborate with product and analytics teams to identify and solve problems through experimentation.
• Calculate and communicate baseline conversion rates, sample sizes, MDE, confidence levels, and statistical power.
• Monitor and validate data quality in ongoing experiments.
• Analyse experiment performance, visualise findings clearly, and present results to product teams and stakeholders.
• Conduct deep-dive analyses to understand performance drivers and propose next iterations.
• Work with the platforms team to continuously improve experimentation capabilities.

Must-Have Qualifications

• Strong SQL skills and experience working with very large, complex datasets.
• Proficiency in statistical analysis and tools (Excel, R, Python).
• Knowledge of statistical, quantitative, and qualitative analytical techniques, including frequentist statistics.
• Experience designing experiments (A/B testing, RCTs) and applying experimental design principles.
• Strong communication skills (written and verbal), with ability to explain complex findings to non-technical audiences.
• High attention to detail and accuracy in data analysis and experiment design.
• Strong problem-solving mindset with innovative approach to complex challenges.
• Experience in digital analytics (reading tracking specs, investigating tracking issues).

Desirable

• Hands-on experience running A/B tests.
• Working knowledge of data visualisation tools (e.g. Tableau).
• Python for analytics and automation.

Level-Specific Requirements

Level 3 (Junior–Mid):

• Proficient in SQL and Excel.
• Familiar with Optimizely, Piano Analytics, Tag Inspector.
• Exposure to Python or R for basic statistical analysis.
• Basic understanding of experimental design and statistics.
• Experience: 1–2 years in a data/analytics role. Works under general direction, escalates complex issues.

Level 4 (Mid–Senior):

• Advanced SQL, experienced with large datasets.
• Proficient in Python or R for statistical modelling.
• Strong knowledge of frequentist statistics & experimental design.
• Skilled in Optimizely, Tableau, and data dictionaries (e.g. Alation).
• Experience: 3–5 years in experimentation or analytics roles. Works with minimal supervision and influences product decisions.

Level 5 (Senior–Lead):

• Expert in SQL, Python/R, and statistical methodologies.
• Deep knowledge of experimentation platforms & digital analytics.
• Strong communication and stakeholder management skills.
• Experience with data visualisation & storytelling.
• Experience: 5+ years in analytics or experimentation leadership roles. Operates with broad autonomy and strategic influence.

Working from home and minimum 2 days per month working from office + if team decides to set some days from the office or some important meetings/client visits, when attendance in office is required.

N-iX is a global software development service company that helps businesses across the world develop successful software products. Founded in 2002, N-iX has come a long way, expanding its presence across Europe, the US, and Latin America. Today, we are a strong community of 2,000+ professionals and a reliable partner for global industry leaders and Fortune 500 companies. 

We are looking for an experienced Head of AI Consulting to head the AI Consulting direction within N-iX’s CTO Office. This is a strategic leadership role where you will shape our AI service offerings, drive technical pre-sales, lead high-impact projects, and build a world-class AI consulting team.

What will you do:

• Lead technical pre-sales as the primary consultant, scoping business and technical requirements for Gen AI (LLM, RAG, Agents), ML, CV, and related AI disciplines
• Become (or be ready to become) a world-class AI consultant for both clients and internal delivery teams
• Engage in short- and mid-term AI projects as a consultant/engineer to ensure successful execution and delivery
• Hire, manage, and mentor a team of AI consultants supporting pre-sales, project initiation, and delivery
• Collaborate with sales and marketing teams to refine and create new AI service offerings
• Partner with our alliances team to maintain and expand strategic partnerships (AWS, GCP, Azure, Nvidia, etc.)

• Report directly to VP of Data and AI Consulting, with dotted line supervision from the CTO of the company.

   

Requirements:

• 7+ years as an AI/ML/CV consultant with experience in pre-sales and delivery of both short- and long-term projects.
• 3+ years managing AI consultants or engineering teams.
• Experience in IT Service Business
• Strong leadership skills with excellent communication and client engagement abilities.

• Broad and deep understanding of AI technologies, trends, and methodologies.

   

What you will get:

• Lead one of N-iX’s most strategic practices within the CTO Office
• Collaborate with world-class clients on complex business and technology challenges (e.g., eBay, Bosch, Siemens, Credit Agricole, Office Depot)

• Build and lead a top-tier AI consulting team of passionate experts.

   

We offer*:

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

• Other location-specific benefits

   

*not applicable for freelancers

We are looking for an ML Engineer to join IntelliArts and become part of a brand-new team building a product for a US-based healthcare AI marketing startup. The solution is being developed from scratch, and you’ll work on cutting-edge ML/LLM applications in a compliance-heavy domain. Together with 4 Full Stack Engineers and another ML Engineer (all based in Ukraine within IntelliArts), you’ll create intelligent systems that make marketing in the pharmaceutical industry both compliant and scalable.

You’ll be working on solutions where marketing materials must align with strict U.S. regulatory standards. The product combines three types of data: clinical trial reports, marketing materials, and regulatory guidelines, enabling LLM-powered compliance checking and fact verification. From digitizing complex PDFs with graphs and tables to comparing claims against trial evidence and highlighting compliance risks, you’ll contribute to building a reliable AI-driven compliance platform.

Responsibilities

• Translate business needs into ML/LLM problems
• Build, validate, and deploy solutions for OCR, fact verification, and compliance checking using LLMs and supporting ML components
• Define evaluation metrics and experimentation loops (e.g., fact-checking accuracy, compliance precision/recall, human-in-the-loop review efficiency)
• Integrate models into microservices and workflows (batch/real-time inference, APIs, containers)
• Establish MLOps foundations: model versioning, CI/CD, monitoring, and drift detection for LLM and OCR components
• Collaborate closely with software engineers, domain experts, and compliance stakeholders to ensure models deliver measurable business and regulatory impact
• Explore opportunities for safe text generation: assisting marketing teams by drafting compliant materials grounded in clinical data and guidelines

Required skills

• 4+ years of hands-on experience in applied machine learning and NLP, with a proven track record in delivering production systems
• Practical experience with LLMs: fine-tuning and prompt design, evaluation methods, and integration via APIs and local model deployments (e.g., HuggingFace, OpenAI, Anthropic)
• Experience working with OCR tools and pipelines, including extracting structured information from scanned PDFs (text, tables, graphs) and transforming it into usable data for downstream tasks
• Experience building and deploying solutions for fact verification, compliance checking, or text classification in real-world workflows
• Strong understanding of LLM evaluation and error analysis, including metrics for compliance, factuality, and hallucination control (precision/recall, F1, factual consistency scores, calibration methods)
• Familiarity with explainability techniques for NLP/LLM systems (attention maps, rationale extraction, human-in-the-loop review)
• Experience with ML/LLM versioning and reproducibility tools (e.g., MLflow, DVC, Weights & Biases)
• Familiarity with cloud-based ML/LLM infrastructure (AWS/GCP/Azure) and containerized deployments
• English Upper-Intermediate (B2) or higher

As a plus

• Experience with retrieval-augmented generation (RAG) for grounding LLM outputs in external sources
• Knowledge of the pharmaceutical or healthcare domain, especially regulatory compliance processes
• Experience building or evaluating fact-checking systems (e.g., claim verification, evidence retrieval, consistency checking)

Personal Profile Overview

• Owning the full ML/LLM lifecycle (problem framing, data preparation, solution design, deployment, monitoring)
• Degree in Data Science, Computer Science, Software Engineering or related field
• Stability in previous employment history, with a tendency to remain with employers for extended periods
• Experience managing diverse project activities (not only coding, but also requirements analysis, estimations, and documentation for compliance-heavy domains)
• Clear and effective communication skills, both verbal and written, and the ability to convey ideas, information, and messages accurately and efficiently to both technical and non-technical stakeholders
• Proficiency in fostering effective collaboration and teamwork activities
• Ability to analyze complex information, assess risks, and make decisions based on sound reasoning and regulatory constraints
• Focus on building trustworthy solutions that prioritize safety and customer satisfaction
• Analytical thinking, problem-solving abilities, and a strategic approach to technical challenges
• Transparency in sharing information within a team and company
• Willingness to acquire new knowledge and insights to enhance professional growth and performance

We offer

• Fuel your professional growth with paid online courses, conferences, certifications, English classes, a corporate library, and a leadership program
• Thrive in a culture of trust and cooperation with no time trackers and minimal bureaucracy
• Enjoy 20 business days of paid vacation, plus state holidays to prioritize your well-being
• Experience an open-door culture, transparent communication, and top management at a handshake distance
• Enjoy comfortable office vibes with no open space policy, relaxing sports areas, a spacious bar/kitchen, and more
• Achieve balance with our hybrid/fully remote work model
• Receive fair and competitive compensation
• Fuel your productivity and foster a sense of community with complimentary daily lunches
• Participate in meaningful initiatives supporting Ukraine’s victory
• Take flexible sick leave without burdensome documentation and access parental benefits
• Choose from comprehensive medical insurance or a sports compensation package
• Have fun with regular team-building activities, corporate events and celebrations, and unique initiatives like Week in Lviv

About the Client and Product:
Our client provides one of the world’s leading online video platforms, designed to power live streaming, online presentations, virtual conferences, events, tutorials, and training sessions. Leveraging advanced browser-based video capture technologies, the platform supports thousands of simultaneous viewers during live events.

Built with state-of-the-art video pipeline technologies—similar to those used by leading organizations like Amazon Video and Netflix—the platform encodes and streams millions of minutes of video content annually, making it a key player in the digital video space.

About the Role:
We are looking for a GenAI Engineer to design, develop, and deploy generative AI solutions. You will work with product teams to integrate AI capabilities, improve automation, and enhance user experiences.

Responsibilities:

• Build, fine-tune, and deploy AI models and pipelines.
• Design scalable AI solutions for text, code, image, or multi-modal generation.
• Evaluate and optimize model performance.
• Collaborate with cross-functional teams on AI integration.

• Mentor junior engineers and share best practices.

   

Requirements:

• 3–7 years of software engineering experience.
• Hands-on experience with AI/ML models, including generative AI.
• Strong software design and problem-solving skills.
• Clear communication and teamwork abilities.

• Upper-Intermediate English or higher. 

   

Preferred:

• Experience with chatbots, content generation, or AI assistants.

• Familiarity with LLMs, embeddings, or retrieval-augmented generation.

   

We Gladly Offer:

• Work in a flexible, Agile, multinational team where innovation and collaboration drive success.
• An opportunity to leverage your skills and experience to build state-of-the-art software products while expanding your expertise in cutting-edge technologies.
• Access to training and continuous learning opportunities to grow your skill set and stay ahead in the evolving tech landscape.
• The chance to work with leading global clients across industries and gain domain expertise in AWS and cloud-based solutions.
• A modern office located in the city center, providing a dynamic and inspiring workspace.
• Flexibility to work both remotely and on-site, allowing you to balance professional and personal commitments effectively.

We are looking for a Senior AI Engineer to lead the development and adoption of AI-driven solutions across the company. This is a hands-on, high-impact role where youll drive innovation, build production-ready systems, and help integrate AI into key business workflows.

     Requirements:

• 6+ years of experience in developing machine learning or AI systems;
• Bachelors degree in Computer Science (or other related degree);
• English level B2+;
• Proven record of deploying production-grade AI/LLM solutions;
• Strong communication and influencing skills;
• Ability to work independently and drive initiatives from scratch;
• Experience with real-time or large-scale AI systems is a big plus.
   

     Responsibilities:

• Design and implement AI solutions leveraging large language models (LLMs) to drive business impact;
• Own the full development cycle from prototype to deployment;
• Build scalable, high-performance AI systems across multiple domains;
• Promote AI adoption through clear value demonstration to stakeholders;
• Collaborate with cross-functional teams to integrate AI into existing workflows;

• Communicate technical results to both technical and non-technical audiences, including C-level.
   

  Technical Skills:

• LLMs: OpenAI, Claude, Gemini, LLaMA.
• Frameworks: LangChain, LangGraph, vLLM, LMDeploy.
• Languages: Python, Java, SQL.
• Solid grasp of MLOps/LLMOps best practices.
• RAG systems and prompt engineering expertise.
• Vector databases: FAISS, Pinecone, Weaviate, Milvus.
• Experience with cloud platforms (AWS, GCP, Azure).
   

     Benefits:

• Great company atmosphere and comfortable communications;
• 20 working days of vacation and 20 sick days;
• Development support;
• Free English classes;
• Financial support for learning;
• Financial support for sports;
• Accounting support.

Location: Remote
Engagement: Contract / Part-time or Full-time
Domain: AI Training, Data Quality, SQL Code Review

About the Role

We are seeking an experienced SQL Code Reviewer to join our AI training QA team. In this role, you will audit annotator evaluations of AI-generated SQL responses and ensure technical correctness, instruction adherence, proof-of-work validation, and consistent application of evaluation rubrics.

This is a critical position that directly contributes to the quality of AI training data, helping improve large language model (LLM) performance for SQL-based tasks.

Responsibilities

• Audit annotator evaluations of AI-generated SQL responses.
• Verify adherence to prompt requirements: query logic, joins, syntax correctness.
• Assess SQL code for correctness, performance, security, and readability.
• Run and validate proof-of-work code submitted by annotators.
• Ensure responses follow instructional guidelines for clarity, style, and tone.
• Identify and document errors, omissions, and rating inconsistencies.
• Provide clear and constructive QA feedback aligned with rubric criteria.
• Collaborate with internal teams to resolve complex or ambiguous cases.

Required Qualifications

• 5–7+ years of professional experience in SQL development, QA, or code review.
• Strong expertise in core SQL concepts and development best practices.
• Experience with debugging, testing tools, and code execution environments.
• Excellent analytical and critical thinking skills.
• Strong written communication for documentation and feedback.
• English proficiency at B2, C1, C2, or Native level.

Preferred Qualifications

• Experience with AI / LLM workflows or human-in-the-loop QA.
• Familiarity with structured code evaluation processes and rubrics.

Responsibilities

Design and develop Agentic AI systems, models, and an advanced

infrastructure stack.

Build product components that integrate with internal systems, user

experience, and advanced security features.

Research new technologies, libraries, and solutions in AI and Cyber domains.

Work in rapid sprints using Agile methodologies.

Collaborate with developers and product teams to improve processes and

design system architecture.

Lead the adoption of advanced technologies and best practices in AI and

Software Engineering.

Requirements and Experience

Bachelor’s/Master’s degree in Computer Science, Engineering, or a related

field.

4+ years of professional experience in software development of medium-to-

large scale systems.

Proven experience with Python, Node.js, NestJS, TypeScript/JavaScript, React, Redis, MongoDB, Kafka, AWS, NX.

Hands-on experience with microservices, Docker, and Kubernetes.

Strong background in software architecture and system design.

Experience with LangGraph and LangChain – mandatory.

Experience developing and integrating with MCP (Model Context Protocol) in

AI – strong advantage.

Familiarity with cybersecurity – strong advantage.

Knowledge in MLOps, fine-tuning, and vector databases – advantage.

Excellent problem-solving skills and ability to thrive under tight deadlines.

Proactive mindset, team player, and ability to provide technical leadership.

Must speak intermediate plus English.

Must be a team player, hard worker, trust worthy, reliable, responsible,

motivated and a long term player.

Impressit is looking for an experienced Senior AI/ML Engineer to lead the development and optimization of our cutting-edge agentic AI architecture. You will work on a sophisticated multi-agent orchestration system that powers intelligent document processing and analysis for commercial banking applications. This role requires deep expertise in LLM integration, distributed systems, and production ML engineering.

What will you do?

- Design and implement intelligent orchestration systems that dynamically route tasks to specialized AI agents based on query analysis
- Develop and optimize RAG (Retrieval-Augmented Generation) pipelines using vector databases and embedding models
- Build production-ready AI agents that leverage multiple LLMs (Claude, GPT, Llama) through AWS Bedrock
- Implement sophisticated prompt engineering strategies and citation tracking systems for accurate, traceable AI responses
- Create scalable distributed architectures using AWS Step Functions, Lambda, and event-driven patterns
- Implement comprehensive logging, monitoring, and error handling for production AI systems

What do we expect?

- 4+ years of experience in ML/AI engineering, with at least 2 years working with LLMs in production
- Strong Python programming skills and experience with modern ML frameworks
- Proven track record of building distributed, event-driven architectures
- Experience with production ML challenges: latency optimization, cost management, error handling
- Strong software engineering practices, including testing, documentation, and code review

As a plus:

- Experience with Agentic AI systems and multi-agent architectures
- Knowledge of financial services or commercial banking domains
- Experience with AWS services (Bedrock, S3, DynamoDB, Lambda, and Step Functions)

At Endgame

• Ability to make an impact: Be part of the company which values results
• Grow fast. Work as a part of a top engineering team
• Build, build, build: start your own pet project, we will mentor and advise
• BYOTS: bring your own tech stack. Ability to explore and influence the decisions
• Perks: laptop, fancy tools, vacations, remote work, all usual stuff
   

Why

• Because 80% of enterprise software is garbage
• Because long discussions without valuable action can be tiresome
• Because small, diverse expert teams outperform armies
• Because we know how to build faster than yesterday
• Because great engineers deserve better

We're building the alternative.
 

What We Do

• Deliver working products, not slides
• Unbreak enterprise software
• Ship in weeks, not quarters
• Smaller teams, senior only
   

The Job

• Build AI systems that actually work in production
• Ship LLM-powered features that solve real problems
• Own the entire pipeline — data → retrieval → prompts → tools → evals → production.
• Ship with guardrails: safety filters, PII handling, audit logs
• Turn messy problems into working AI features (LLMs, RAG, agents)
• Choose models and stack pragmatically (build, buy, or fine‑tune)
• Optimize cost, latency, and reliability (caching, batching, streaming)
• Measure everything: offline eval harness + online A/Bs
• Talk to clients about what's possible, not what's hype
• Code. No hand‑offs
• No bureaucracy
   

You

• Shipped AI/ML systems in production (not just demos)
• Built systems that scale beyond ChatGPT copy-paste
• Built RAG systems that actually retrieve the right context
• Experience with real-world LLM ops — monitoring, evaluation, cost optimization
• Fixed more weird failures than you caused (hallucinations, drift, token limits)
• Senior or higher; strong product taste and bias to action
• Communicate clearly — explain transformers to CEOs and tokens to engineers
• Obsessed with making AI useful, not just clever
• Treat prompts/data like code — versioned, tested, reproducible
• Own what you ship — from system prompt to API response
   

Your Stack and Experience

• Deployed and maintained LLM applications in production environments
• Proficiency with: Python, LLM SDKs (OpenAI/Anthropic/Azure/Bedrock/Cohere), orchestration & agents (LangChain/LangGraph or equivalent)
• Experience with vector databases (Pinecone, Qdrant, pgvector)
• Evals & observability: Ragas/TruLens, Langfuse/Helicone, OpenTelemetry
• Big plus: Workflow automation and low-code AI tools (n8n, Langflow, Flowise)
• Prompt engineering, function calling, agent frameworks — the whole toolkit
• Big plus: ML experience and TensorFlow knowledge for when LLMs aren't the answer
   

We Don't Want

• Process evangelists
• Architecture astronauts
• Meeting enthusiasts
• Supervision required
   

The Deal

• Competitive Salary
• Good bonus
• Decent learning budget
• AI tools
• Remote with occasional travel

Anything missing, tell us.
 

FAQ

Q: Remote?
A: Yes. Anywhere CET +/- 2 hours.

Q: Work-life balance?
A: Work hard. Rest well. No weekends unless prod is on fire.

Q: Growth path?
A: Build products → Run practices → Build the company

Q: Why "Endgame"?
A: Because we're building what comes next.
 

That's it.
You either get it or you don't.
If you get it, we should talk.
 

Equal opportunity employer.
We judge only on ability to ship products.

About the Project

Join a high-performing UK-based product and cross-functional product team composed of top-tier engineers(PhD holders). We’re building an enterprise-grade data platform designed to integrate, process, and analyze vast amounts of disparate data in real-time.

This platform leverages cutting-edge technologies: Big Data, cloud-native architecture, AI-driven insights, and advanced database tooling to deliver deep operational visibility and power faster, smarter business decisions. We ensure scalability, traceability, and compliance (GDPR, HIPAA) through robust data lineage and governance features.

You’ll work mainly on AI services, having tight collaboration with backend developers to ensure seamless API integration. 

What You’ll Do

• Design and develop advanced AI components using LangChain, AutoGen, and other multi-agent orchestration frameworks
• Build and optimize RAG (Retrieval-Augmented Generation) pipelines using tools like Google AI Platform, Vertex AI and Pinecone.
• Engineer efficient prompts and fine-tune LLMs (e.g., GPT-4o, DeepSeek) for advanced data analytics capabilities
• Develop AI-related backend services using Python and FastAPI
• Deploy scalable solutions in Google Cloud Platform (GCP), working with services such as BigQuery, GKE, Cloud Storage, etc.

• Collaborate with backend and data engineering teams to integrate and expose AI functionality via well-structured APIs

   

Must-Have Skills

• 5+ years of experience in backend and AI system development
• Strong hands-on experience with LangChain, AutoGen, and multi-agent frameworks
• In-depth knowledge of LLMs, prompt engineering, NL2SQL, and RAG architectures
• Proficient in Python and FastAPI
• Proven experience with GCP services: Vertex AI, BigQuery, GKE, Cloud Storage
• Experience building production-grade RAG pipelines

• Excellent problem-solving and communication skills

   

Nice-to-Have

• Experience working with data engineering and DevOps tools
• Familiarity with data governance frameworks and compliance standards (GDPR, HIPAA)

• Exposure to real-time processing and scalable architecture patterns

   

Why Join Us

• Work with a world-class team on a cutting-edge AI and data platform
• High-impact role with room for innovation and growth
• Flexible schedule and remote-friendly setup
• Competitive compensation
• Collaborative, growth-oriented culture
• Engage in technically challenging, meaningful projects

We are looking for a proactive and technically strong Middle AI Engineer who is passionate about Agentic AI and ready to drive innovation across our product ecosystem. In this role, you will take ownership of designing and building autonomous AI agents, integrating AI capabilities into real product workflows, and delivering production-ready solutions with tangible business value. 

Requirements
- 3+ years of experience in Python development.
- Experience with LLMs, transformers, and NLP models.
- Proven experience with LangGraph, LangChain, or similar frameworks for agent-based design.
- Understanding and practical experience with RAG pipelines and vector databases (e.g. Qdrant)
- Experience with PyTorch or TensorFlow.
- Strong problem-solving skills and a business-oriented mindset.
- Ability to work in a fast-paced, evolving environment with cross-functional teams.

Nice to Have
- Familiarity with MLOps practices, containerization (Docker), and deploying scalable AI solutions.
- Understanding of multi-agent orchestration, self-healing logic, and autonomous systems.
- Experience in e-commerce, PIM systems, or digital content workflows.
- PHP knowledge for integration support.
- Fluent English

What You’ll Be Doing / Responsibilities:
- Design, build, and fine-tune LLMs and AI agents using LangGraph, LangChain, or similar frameworks.
- Integrate AI-driven features into our PIM, focusing on real-world use cases in e-commerce.
- Collaborate with product and engineering teams to identify opportunities and deliver AI-driven solutions.
- Advocate for best practices in AI implementation and promote adoption across teams.

If you are AI-focused, business-driven, and eager to work on cutting-edge technology, we’d love to hear from you! 🚀

What we offer:

Professional development
- PDP (Personal Development Plan) and PIP (Performance Improvement Plan) processes to foster professional growth.
 - Education allowance for continuous learning and development.
- Improving the internal AI laboratory.
 - Individual English lessons to enhance language skills.

• Work environment and flexibility
  - Autonomy in decision-making and strategy implementation.
   - Remote work options or a well-equipped office near Livoberezhna metro station.
   - Starlink internet, generator, and a comfortable work environment.
• Health and well-being
  - Medical insurance (coverage only within Ukraine)
   - Mental health support through Pleso (psychotherapy).
   - Generous vacation and sick leave policy to ensure work-life balance.
• Team culture
  - Regular corporate events and team activities to build connections and foster collaboration.