Senior AI Engineer - Agentic AI

EPAM Systems; Greater London; Hybrid; GBP 90,000 - 130,000; Full time

Benefits offered by this job

ESPP

Life assurance and income protection

Private medical insurance

Dental care

Employee Assistance Program

Pension plan

Cyclescheme, Techscheme and season-tix

On-site perks (lunch, massages, events

Job summary

EPAM Systems in London, UK, is seeking a Senior AI Engineer specializing in Agentic AI to design scalable platforms that integrate LLMs, multi-agent orchestration, and RAG patterns for production-ready enterprise solutions.

You will build reusable components, orchestration engines, and governance frameworks to enable secure, scalable AI workflows. Hybrid work mode in London offers opportunities to influence platform engineering across projects.

Qualifications

• Bachelor's or Master's degree in Computer Science, Engineering or related field.
• Practical experience delivering Generative AI or Agentic AI systems into production.
• Expertise in Python engineering for APIs, microservices, testing and CI/CD workflows.
• Strong working knowledge of LLM capabilities, including prompt design, structured outputs, tool calling and retrieval strategies.
• Hands-on experience with agent orchestration frameworks (LangGraph, AutoGen, CrewAI or Semantic Kernel).
• Proven experience with RAG implementations, embeddings and vector database integrations.
• Familiarity with stateful or long-running systems, including checkpointing and resumable workflows.
• Cloud deployment experience (Azure preferred), using services such as Azure OpenAI, AI Foundry or AI Search, with Docker and Kubernetes.
• Understanding of schema validation frameworks (e.g., JSON Schema, Pydantic) and MLOps tools such as MLflow or Airflow.
• Strong communication ability to explain trade-offs around cost, latency and accuracy to technical and non-technical audiences.

Responsibilities

• Design, build and deploy Generative AI and Agentic AI solutions from prototype to production
• Implement multi-agent orchestration patterns using frameworks such as LangGraph, CrewAI, AutoGen, Semantic Kernel or OpenAI Agents SDK
• Develop the orchestration backbone for advanced workflows including planning, checkpointing, retries, fallback handling and resumption of long-running processes
• Build and optimize RAG pipelines, including chunking strategies, embeddings, vector/hybrid search and retrieval evaluation with grounded responses and citations
• Develop memory and context management solutions, including short-term and long-term stores and compaction strategies
• Write robust Python APIs and services (e.g., FastAPI), incorporating async execution, background jobs and containerized deployments
• Integrate enterprise systems and tools using protocols such as MCP, A2A, OpenAPI, REST and gRPC, ensuring graceful degradation and retries
• Apply enterprise security and governance practices including RBAC, prompt safety checks, traceability and secrets management
• Implement evaluation pipelines and observability frameworks using tools such as Langfuse, Arize or OpenTelemetry
• Contribute to architectural design decisions, code reviews and engineering standards for platform development

Skills

Python

LLMs

API design

CI/CD

Distributed systems

Communication

Education

Bachelor's or Master's in Computer Science or Engineering

PhD is a plus

Tools

LangGraph

AutoGen

CrewAI

Semantic Kernel

OpenAI Agents SDK

FastAPI

Docker

Kubernetes

Langfuse

OpenTelemetry

MLflow

Airflow

Job description

We're looking for a Senior AI Engineer – Agentic AI to join our team in London, UK in a hybrid working mode.

In this role, you will design and build scalable agentic AI platforms that integrate Large Language Models (LLMs), multi-agent orchestration and retrieval-augmented generation (RAG) patterns into production-ready enterprise solutions. You will focus on creating reusable platform components, orchestration engines and governance frameworks that allow complex AI workflows to operate securely and efficiently at scale.

You will be responsible for developing advanced orchestration capabilities, implementing evaluation and observability tooling and embedding enterprise controls for compliance and safety. If you are passionate about innovating with AI in real-world applications and scaling intelligent systems, this role offers an opportunity to make a significant impact in production-grade AI engineering.

Responsibilities

• Design, build and deploy Generative AI and Agentic AI solutions from prototype to production
• Implement multi-agent orchestration patterns using frameworks such as LangGraph, CrewAI, AutoGen, Semantic Kernel or OpenAI Agents SDK
• Develop the orchestration backbone for advanced workflows including planning, checkpointing, retries, fallback handling and resumption of long-running processes
• Build and optimize RAG pipelines, including chunking strategies, embeddings, vector/hybrid search and retrieval evaluation with grounded responses and citations
• Develop memory and context management solutions, including short-term and long-term stores and compaction strategies
• Write robust Python APIs and services (e.g., FastAPI), incorporating async execution, background jobs and containerized deployments
• Integrate enterprise systems and tools using protocols such as MCP, A2A, OpenAPI, REST and gRPC, ensuring graceful degradation and retries
• Apply enterprise security and governance practices including RBAC, prompt safety checks, traceability and secrets management
• Implement evaluation pipelines and observability frameworks using tools such as Langfuse, Arize or OpenTelemetry
• Contribute to architectural design decisions, code reviews and engineering standards for platform development

Requirements

• Bachelor's or Master's degree in Computer Science, Engineering or related field (PhD is a plus)
• Practical experience delivering Generative AI or Agentic AI systems into production environments
• Expertise in Python engineering for APIs, microservices, testing and CI/CD workflows
• Strong working knowledge of LLM capabilities, including prompt design, structured outputs, tool calling and retrieval strategies
• Hands-on experience with agent orchestration frameworks (LangGraph, AutoGen, CrewAI or Semantic Kernel)
• Proven experience with RAG implementations, embeddings and vector database integrations
• Familiarity with stateful or long-running systems, including checkpointing and resumable workflows
• Cloud deployment experience (Azure preferred), using services such as Azure OpenAI, AI Foundry or AI Search, with Docker and Kubernetes
• Understanding of schema validation frameworks (e.g., JSON Schema, Pydantic) and MLOps tools such as MLflow or Airflow
• Strong communication ability to explain trade-offs around cost, latency and accuracy to technical and non-technical audiences

Nice to have

• Experience using Azure AI Foundry or Microsoft Agent Framework
• Knowledge of MCP and A2A protocols for agent and tool interoperability
• Hands-on work with vector databases like Pinecone, Weaviate, Qdrant or pgvector
• Familiarity with distributed systems, workflow engines (Temporal, Airflow or Dagster) and event-driven architectures
• Experience with open-source LLMs or Small Language Models for custom deployments
• Knowledge of AI safety and governance: guardrails, output filtering and red-teaming practices
• Background in fine-tuning or adapting foundation models (e.g., LoRA, distillation) for domain-specific tasks

We offer

• EPAM Employee Stock Purchase Plan (ESPP)
• Protection benefits including life assurance, income protection and critical illness cover
• Private medical insurance and dental care
• Employee Assistance Program
• Competitive group pension plan
• Cyclescheme, Techscheme and season ticket loans
• Various perks such as free Wednesday lunch in-office, on-site massages and regular social events
• Learning and development opportunities including in-house training and coaching, professional certifications, and courses
• If otherwise eligible, participation in the discretionary annual bonus program
• If otherwise eligible and hired into a qualifying level, participation in the discretionary Long-Term Incentive (LTI) Program