Senior AI/Data Science Consultant

Hybrid in The United Kingdom: LondonData Science ConsultingapplyWe'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.ResponsibilitiesDesign, build, and deploy Generative AI and Agentic AI solutions through the full lifecycle from prototype to productionImplement and optimize multi-agent systems using frameworks such as LangGraph, CrewAI, AutoGen, Semantic Kernel, or OpenAI Agents SDKCreate orchestration patterns including planner/executor, supervisor/worker, and tool-calling workflowsBuild RAG pipelines with embeddings, chunking strategies, hybrid search, retrieval evaluation, and enterprise data groundingArchitect reusable AI design patterns including human-in-the-loop workflows and multi-agent coordination modelsApply agent integration and communication standards (MCP, A2A, OpenAPI, REST, gRPC)Lead technical delivery of AI projects, managing timelines, dependencies, and stakeholder expectationsEnsure delivery adheres to AI governance, data privacy, and regulatory frameworksSupport pre-sales activities through technical solutioning, demos, and PoC developmentApply observability and monitoring using tools like Langfuse, Arize, and OpenTelemetryContribute to architecture decisions and technical standards across engagementsRequirements6+ years in AI/ML engineering, data science, or applied AI roles within professional services or enterprise environmentsProven experience building and deploying Generative AI and Agentic AI solutions into productionExpertise in LLMs, advanced RAG strategies, prompt engineering, and model evaluation approachesHands-on experience with multi-agent orchestration frameworks (LangGraph, CrewAI, AutoGen, Semantic Kernel)Familiarity with orchestration protocols such as MCP, A2A, and OpenAPI-based integrationStrong Python development skills and knowledge of CI/CD, DevOps, and cloud-native architecturesPractical experience with Azure (Azure OpenAI, Azure AI Foundry, AI Search) and familiarity with AWS or GCPProficiency with containerized deployment, MLOps tooling (MLFlow, Airflow), and infrastructure-as-code practicesBachelor’s or Master’s degree in Computer Science, Data Science, or related fieldNice to haveExperience with Azure AI Agent Service or Microsoft Agent FrameworkFamiliarity with vector databases (Pinecone, Weaviate, Qdrant, Milvus)Knowledge of AI safety techniques such as guardrails, bias mitigation, and model explainabilityUnderstanding of Intelligent Document Processing, data lineage, and distributed memory for agent systemsExperience enabling responsible and auditable AI governanceOUR BRANDS