Senior AI Engineer Data Scientist

Were looking for a Senior AI Engineer / Data Scientist to join our team in London United Kingdom in a hybrid working mode. This role is at the core of EPAMs Data & AI Practice and focuses on building state-of-the-art Generative AI Agentic AI and advanced data science solutions for real-world business problems. Youll design and develop multi-agent systems implement RAG pipelines and deliver production-ready AI applications that transform client capabilities across multiple industries. If youre passionate about pushing the frontiers of LLMs orchestration frameworks and scaling AI systems into production this opportunity offers a high-growth environment and cutting-edge challenges.

• 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

• Bachelors/Masters 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)

• 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