Senior AI Engineer / Data Scientist

• Design, build, and deploy Generative AI and Agentic AI solutions from prototyping through production
• Develop and optimize multi-agent systems using frameworks such as LangGraph, CrewAI, AutoGen, and Semantic Kernel
• Implement orchestration patterns including planner/executor, supervisor/worker, and tool-calling workflows
• Design and build RAG pipelines, including embeddings, chunking, hybrid search, and retrieval evaluation for enterprise data grounding
• Develop orchestration engines supporting multi-step planning, delegation, and fallback paths for agent workflows
• Implement integration and communication patterns via MCP, A2A, OpenAPI, REST, and gRPC
• Build production-grade Python APIs and microservices integrating with enterprise systems and AI services
• Apply observability and monitoring solutions (Langfuse, Arize, Grafana) to ensure system reliability
• Contribute to solution architecture, best engineering practices, and documentation

Do you have experience in gRPC?, Do you have a Master’s degree?, * Bachelor’s/Master’s in Computer Science, Data Science, or related field with 4+ years’ experience, or Ph.D. with relevant experience

• Strong engineering experience with Python, APIs, microservices, debugging, and code review
• Proven experience building and deploying Generative AI or Agentic AI applications in production
• Deep understanding of LLM concepts, RAG patterns, prompt design, and evaluation methodologies
• Experience with multi-agent orchestration frameworks (LangGraph, CrewAI, AutoGen, Semantic Kernel)
• Familiarity with orchestration strategies like planner/executor and tool calling
• Knowledge of MCP, A2A protocols, and OpenAPI-based integration methods
• Strong experience with cloud environments, ideally Azure (Azure OpenAI, AI Foundry, AI Search)
• Competence in containerized deployments, CI/CD, and MLOps tooling (MLFlow, Airflow)

Nice to have

• Experience with Microsoft Agent Framework, Azure AI Agent Service
• Knowledge of vector databases (Pinecone, Weaviate, Qdrant, Milvus)
• Familiarity with guardrail and AI safety techniques (output filtering, prompt injection defense)
• Experience in distributed systems, event-driven architectures, and workflow engines
• Prior involvement in training, fine-tuning, or experimenting with foundation models

Pulled from the full job description

• Employee stock purchase plan
• Employee assistance programme
• Company pension
• Private medical insurance
• Cycle to work scheme
• Tech scheme, * EPAM Employee Stock Purchase Plan (ESPP)
• Protection benefits including life assurance, income protection and critical illness cover
• Private medical insurance and dental care
• Employee Assistance Program
• Competitive group pension plan
• Cyclescheme, Techscheme and season ticket loans
• Various perks such as free Wednesday lunch in-office, on-site massages and regular social events
• Learning and development opportunities including in-house training and coaching, professional certifications, and courses
• If otherwise eligible, participation in the discretionary annual bonus program
• If otherwise eligible and hired into a qualifying level, participation in the discretionary Long-Term Incentive (LTI) Program