AI Engineer - Agentic AI & Back End
We’re looking for a Senior AI Engineer – Agentic AI & Backend to join our team in London, United Kingdom in a hybrid working mode. This role is part of EPAM’s Data & AI Practice and focuses on building practical AI solutions that move clients from concept to production-ready systems. You will work across sectors such as Financial Services, CPG and Retail, helping design and implement AI-powered workflows and backend services that deliver measurable business outcomes. This position offers an opportunity to work on innovative AI technologies, backend architectures, and real-world agentic systems in enterprise environments.
Responsibilities
- Design and implement AI solutions, focusing on agentic workflows and backend engineering
- Build backend services and APIs in Python using frameworks such as FastAPI or similar
- Develop orchestration patterns for agentic workflows, including intent classification, tool calling, routing and supervisor/worker flows
- Create and maintain AI tools and skills with clear interfaces, testing and secure execution
- Configure and integrate MCP servers and clients for enterprise-grade agent connectivity
- Develop RAG-based solutions, including GraphRAG and Agentic RAG, aligned with client requirements
- Work with agent frameworks and SDKs such as Pydantic AI, LangGraph/LangChain or Microsoft agent platforms
- Define evaluation strategies for agentic systems using automated and human-in-the-loop methods
- Implement telemetry and observability solutions to monitor performance and quality
- Leverage AI-assisted tools such as Claude Code, OpenAI Codex or GitHub Copilot to accelerate development
Requirements
- Bachelor’s or Master’s degree in Computer Science, Engineering, or related field with 4+ years of hands-on ML/AI engineering experience (or PhD with relevant experience).
- Strong Python development skills with proven backend engineering experience
- Hands-on experience building agentic or LLM-powered applications beyond simple prototypes
- Knowledge of API design, asynchronous processing, testing, debugging and production reliability
- Experience with Azure or AWS cloud environments and related services
- Familiarity with agent workflows, orchestration patterns and tool-calling techniques
- Experience integrating MCP or building RAG-based solutions with quality evaluation mechanisms
- Understanding of evaluation methodologies for AI systems such as golden datasets and automated tests
- Proficiency in telemetry, logging and observability tools for production systems
- Ability to work in cross-functional client engagement teams delivering enterprise solutions
Nice to have
- Experience using AI development tools such as Claude Code, OpenAI Codex or GitHub Copilot
- Exposure to Azure AI Search, Azure Application Insights, Amazon Bedrock or other cloud AI services
- Familiarity with Microsoft 365 Agents SDK, Copilot SDK or enterprise Copilot extensions
- Knowledge of AI safety practices, guardrails and secure execution for AI workflows
- Prior consulting or client-facing experience in enterprise AI solution delivery
