Senior AI/Data Science Consultant
We're looking for a Senior AI Engineer & Data Science Consultant to join our team in London, United Kingdom in a hybrid working mode. This role is part of EPAM’s Data & AI Practice and combines hands-on engineering leadership with technical consulting expertise. You will design and deliver production-grade Generative AI and Agentic AI solutions while engaging stakeholders and shaping strategic AI initiatives.
If you’re passionate about multi-agent systems, advanced RAG pipelines, and delivering end-to-end AI solutions that create measurable business impact, this role offers both technical depth and leadership scope.
Responsibilities Design, build, and deploy Generative AI and Agentic AI solutions through the full lifecycle from prototype to production Implement and optimize multi-agent systems using frameworks such as LangGraph, CrewAI, AutoGen, Semantic Kernel, or OpenAI Agents SDK Create orchestration patterns including planner/executor, supervisor/worker, and tool-calling workflows Build RAG pipelines with embeddings, chunking strategies, hybrid search, retrieval evaluation, and enterprise data grounding Architect reusable AI design patterns including human-in-the-loop workflows and multi-agent coordination models Apply agent integration and communication standards (MCP, A2A, OpenAPI, REST, gRPC) Lead technical delivery of AI projects, managing timelines, dependencies, and stakeholder expectations Ensure delivery adheres to AI governance, data privacy, and regulatory frameworks Support pre-sales activities through technical solutioning, demos, and PoC development Apply observability and monitoring using tools like Langfuse, Arize, and OpenTelemetry Contribute to architecture decisions and technical standards across engagements Requirements 6+ years in AI/ML engineering, data science, or applied AI roles within professional services or enterprise environments Proven experience building and deploying Generative AI and Agentic AI solutions into production Expertise in LLMs, advanced RAG strategies, prompt engineering, and model evaluation approaches Hands-on experience with multi-agent orchestration frameworks (LangGraph, CrewAI, AutoGen, Semantic Kernel) Familiarity with orchestration protocols such as MCP, A2A, and OpenAPI-based integration Strong Python development skills and knowledge of CI/CD, DevOps, and cloud-native architectures Practical experience with Azure (Azure OpenAI, Azure AI Foundry, AI Search) and familiarity with AWS or GCP Proficiency with containerized deployment, MLOps tooling (MLFlow, Airflow), and infrastructure-as-code practices Bachelor’s or Master’s degree in Computer Science, Data Science, or related field Nice to have Experience with Azure AI Agent Service or Microsoft Agent Framework Familiarity with vector databases (Pinecone, Weaviate, Qdrant, Milvus) Knowledge of AI safety techniques such as guardrails, bias mitigation, and model explainability Understanding of Intelligent Document Processing, data lineage, and distributed memory for agent systems Experience enabling responsible and auditable AI governance
