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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior AI Engineer / Data Scientist - **Company:** EPAM Systems, Inc. - **Location:** London, UK - **Experience:** Expert - **Salary:** £98,186.0 - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Airflow, Microsoft Azure, Code Review, Continuous Integration, Software Debugging, Distributed Systems, Python (Programming Language), Software Safety, Search Technologies, Openapi, Cloud Platform System, Large Language Models, Grafana, Multi-Agent Systems, Prompt Engineering, Reliability of Systems, Generative AI, Event Driven Architecture, Build Management, Containerization, AI Platforms, Kubernetes, Information Technology, Machine Learning Operations, Virtual Agents, Microservices - **Published:** July 24, 2026 - **Apply:** https://www.adzuna.co.uk/jobs/details/5810895263 ## About the Role * Bachelor's/Master's in Computer Science, Data Science, or related field with 4+ years' experience, or Ph.D. with relevant experience * Strong engineering experience with Python, APIs, microservices, debugging, and code review * Proven experience building and deploying Generative AI or Agentic AI applications in production * Deep understanding of LLM concepts, RAG patterns, prompt design, and evaluation methodologies * Experience with multi-agent orchestration frameworks (LangGraph, CrewAI, AutoGen, Semantic Kernel) * Familiarity with orchestration strategies like planner/executor and tool calling * Knowledge of MCP, A2A protocols, and OpenAPI-based integration methods * Strong experience with cloud environments, ideally Azure (Azure OpenAI, AI Foundry, AI Search) * Competence in containerized deployments, CI/CD, and MLOps tooling (MLFlow, Airflow) Nice to have * Experience with Microsoft Agent Framework, Azure AI Agent Service * Knowledge 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 engines * Prior involvement in training, fine-tuning, or experimenting with foundation models ## Description * Design, build, and deploy Generative AI and Agentic AI solutions from prototyping through production * Develop and optimize multi-agent systems using frameworks such as LangGraph, CrewAI, AutoGen, and Semantic Kernel * Implement orchestration patterns including planner/executor, supervisor/worker, and tool-calling workflows * Design and build RAG pipelines, including embeddings, chunking, hybrid search, and retrieval evaluation for enterprise data grounding * Develop orchestration engines supporting multi-step planning, delegation, and fallback paths for agent workflows * Implement integration and communication patterns via MCP, A2A, OpenAPI, REST, and gRPC * Build production-grade Python APIs and microservices integrating with enterprise systems and AI services * Apply observability and monitoring solutions (Langfuse, Arize, Grafana) to ensure system reliability * Contribute to solution architecture, best engineering practices, and documentation ## Related Videos - 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