Senior AI Engineer / Data Scientist

Back to SearchLooking for something else Find a vacancy that works for you. Send us your CV to receive a personalized offer.Find me a jobWe're 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 EPAM's 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. You'll design and develop multi-agent systems, implement RAG pipelines, and deliver production-ready AI applications that transform client capabilities across multiple industries. If you're 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 productionDevelop and optimize multi-agent systems using frameworks such as LangGraph, CrewAI, AutoGen, and Semantic KernelImplement orchestration patterns including planner/executor, supervisor/worker, and tool-calling workflowsDesign and build RAG pipelines, including embeddings, chunking, hybrid search, and retrieval evaluation for enterprise data groundingDevelop orchestration engines supporting multi-step planning, delegation, and fallback paths for agent workflowsImplement integration and communication patterns via MCP, A2A, OpenAPI, REST, and gRPCBuild production-grade Python APIs and microservices integrating with enterprise systems and AI servicesApply observability and monitoring solutions (Langfuse, Arize, Grafana) to ensure system reliabilityContribute to solution architecture, best engineering practices, and documentationBachelor's/Master's in Computer Science, Data Science, or related field with 4+ years' experience, or Ph.D. with relevant experienceStrong engineering experience with Python, APIs, microservices, debugging, and code reviewProven experience building and deploying Generative AI or Agentic AI applications in productionDeep understanding of LLM concepts, RAG patterns, prompt design, and evaluation methodologiesExperience with multi-agent orchestration frameworks (LangGraph, CrewAI, AutoGen, Semantic Kernel)Familiarity with orchestration strategies like planner/executor and tool callingKnowledge of MCP, A2A protocols, and OpenAPI-based integration methodsStrong 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 ServiceKnowledge 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 enginesPrior involvement in training, fine-tuning, or experimenting with foundation models