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EPAM Systems
AI

Senior AI Engineer / Data Scientist

EPAM Systems · London, ENG, GB

Actively hiring Posted about 1 month ago

Responsibilities

  • 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

Basic qualifications

  • 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)

Preferred qualifications

  • 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
  • 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

Tags & focus areas

Used for matching and alerts on DevFound
Ai Ai Engineer Data Science Generative Ai
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