Machine Learning Engineer

We’re looking for a Machine Learning Engineer to join EPAM in London, United Kingdom, in a hybrid working mode. You will contribute to an enterprise AI program for one of our clients by building and surfacing MCP Servers and Tools via the internal MCP Gateway and implementing evaluation mechanisms for large language models and agent-based systems. This is a highly technical role combining backend engineering, AI architecture, and enterprise integration to deliver scalable AI solutions.As an AI Engineer, you will work on intelligent enterprise enablement through Model Context Protocol (MCP) integrations and advanced agent frameworks. The role involves API development with FastAPI, deployment of containerized systems, and implementing large language model (LLM) strategies such as prompt engineering and RAG (Retrieval-Augmented Generation). The successful candidate will operate in a Classic Agile environment to design, develop, and optimize next-generation enterprise AI capabilities.ResponsibilitiesBuild and surface MCP Servers and Tools using the internal MCP GatewayDevelop APIs and service endpoints with FastAPI for MCP integrationsImplement agent and LLM frameworks (e.g., LangChain, LangGraph) to enable sophisticated AI workflowsApply prompt engineering strategies and build RAG-based architecture for enhanced response accuracyAutomate quality controls and develop evaluation systems for LLM reliability and performanceContainerize and orchestrate AI services using Kubernetes for scalable deploymentCollaborate cross-functionally with product, QA, and architecture teams to ensure secure, enterprise-grade solutionsMaintain documentation for MCP integrations, testing pipelines, and workflow standardsIntegrate CI/CD practices to streamline deployment and testing processesRequirementsStrong programming experience in Python for backend development and automationExpertise in REST API development using FastAPI for production-scale servicesFamiliarity with Model Context Protocol (MCP) standards, server/client patternsWorking knowledge of LLM/agent frameworks such as LangChain or LangGraphUnderstanding of containerization and orchestration tools like KubernetesAbility to implement prompt engineering principles and RAG-based solutionsSolid grasp of Agile delivery models, CI/CD workflows, and secure coding practicesExcellent problem-solving and cross-team communication skillsNice to haveExperience with observability and monitoring tools for AI-driven workloadsFamiliarity with vector databases for semantic search and retrievalKnowledge of cloud platforms (AWS, GCP, Azure) and GPU-accelerated computeBackground designing evaluation frameworks for AI model performanceExposure to large-scale AI deployment in enterprise environmentsWe offerEPAM Employee Stock Purchase Plan (ESPP)Protection benefits including life assurance, income protection and critical illness coverPrivate medical insurance and dental careEmployee Assistance ProgramCompetitive group pension planCyclescheme, Techscheme and season ticket loansVarious perks such as free Wednesday lunch in-office, on-site massages and regular social eventsLearning and development opportunities including in-house training and coaching, professional certifications, and coursesIf otherwise eligible, participation in the discretionary annual bonus programIf otherwise eligible and hired into a qualifying level, participation in the discretionary Long-Term Incentive (LTI) Program#J-18808-Ljbffr…