AI / Machine Learning Engineer – Agentic LLM Systems (Contract)

Experis UK; Greater London; Hybrid; GBP 70,000 - 110,000; Part time

Benefits offered by this job

Hybrid work model

London office option

Job summary

Experis UK in London seeks an experienced ML/AI Engineer to design, build, and scale agentic LLM systems for production-grade environments. You will collaborate with researchers and engineers to create robust tool-calling, planning, and orchestration frameworks, while integrating multiple LLM providers.

The role emphasizes developing backend services, RAG pipelines, and scalable AI-driven workflows, with a focus on reliability, latency, and cost optimization across enterprise data landscapes.

Qualifications

• 4+ years’ experience in ML/AI engineering.
• Proven hands-on experience building LLM agents, RAG systems, or orchestrated AI workflows in production.
• Strong Python experience.
• Experience with cloud platforms and containerised systems (Docker/Kubernetes) and APIs.

Responsibilities

• Design and build tools, workflows, and infrastructure for agentic LLM systems.
• Develop RAG pipelines, embeddings workflows, and retrieval systems for enterprise data.
• Diagnose and fix failures in agent-generated code and workflows.
• Build frameworks for tool-calling, multi-step planning, orchestration, and agent routing.
• Integrate with LLM providers and support multi-model usage.
• Develop backend services and APIs to support AI-driven applications and workflows.
• Run experiments to improve reliability, latency, cost, and success rates.
• Contribute to evaluation frameworks, observability, and monitoring of performance.

Skills

ML/AI engineering

LLM agents

RAG systems

Python

APIs & microservices

Cloud platforms

Docker & Kubernetes

CI/CD pipelines

Experimentation & metrics

Observability tools

Tools

LangChain

LangGraph

AutoGen

Docker

Kubernetes

Job description

AI / Machine Learning Engineer – Agentic LLM Systems (Contract)

We’re working with a leading tech organisation building next-generation agentic AI systems – LLMs that can plan, reason, call tools, and write/execute code. We’re hiring a Machine Learning Engineer to help design, build, and scale these systems into production-grade, enterprise environments.

You will:

• Design and build tools, workflows, and infrastructure for agentic LLM systems


• Develop RAG pipelines, embeddings workflows, and retrieval systems for enterprise data


• Work with researchers and engineers to diagnose and fix failures in agent-generated code and workflows


• Build frameworks for tool-calling, multi-step planning, orchestration, and agent routing


• Integrate with LLM providers (OpenAI, Anthropic, Vertex AI, open-source models) and support multi-model usage


• Develop backend services and APIs to support AI-driven applications and workflows


• Build and run experiments to improve reliability, latency, cost, and success rates


• Contribute to evaluation frameworks, observability, and monitoring of LLM/agent performance

What We’re Looking For:

• 4+ years’ experience in ML/AI engineering (LLMs, recommender systems, optimisation, or similar)


• Proven hands‑on experience building LLM agents, RAG systems, or orchestrated AI workflows in production


• Strong Python (with PyTorch, TensorFlow, or similar frameworks)


• Experience with agent frameworks (LangChain, LangGraph, AutoGen, or similar)


• Solid understanding of APIs, backend services, and microservices architectures


• Experience working with cloud platforms (AWS, GCP, or Azure) and containerised systems (Docker, Kubernetes)


• Familiarity with event-driven or serverless architectures


• Experience with CI/CD pipelines, testing, and infrastructure as code


• Experience running and analysing large‑scale experiments and performance metrics (latency, accuracy, cost)


• Exposure to monitoring/observability tools for production systems

Nice to Have:

• Experience with multi‑agent systems or distributed AI architectures


• Familiarity with vector databases (Pinecone, Weaviate, OpenSearch, etc.)


• Experience integrating AI systems into enterprise platforms or business workflows


• 6 Months Initial Contract | + Extensions


• Hybrid | London