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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior AI/Data Science Consultant - **Company:** EPAM Systems, Inc. - **Location:** London, UK - **Experience:** Expert - **Salary:** £85,114.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Airflow, Amazon Web Services, Microsoft Azure, Cloud Engineering, Continuous Integration, Software Design Patterns, DevOps, Python (Programming Language), Machine Learning, Software Safety, Search Technologies, Openapi, Large Language Models, Multi-Agent Systems, Prompt Engineering, Model Validation, Generative AI, Kubernetes, Infrastructure Automation Frameworks, Information Technology, Data Lineage, Machine Learning Operations, Virtual Agents - **Published:** July 24, 2026 - **Apply:** https://www.adzuna.co.uk/jobs/details/5810895265 ## About the Role * 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 ## Description * 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 ## Related Videos - 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