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

NLP PEOPLE; Greater London; Hybrid; GBP 101,000 - 129,000; Full time

Job summary

Experis UK is hiring an AI / Machine Learning Engineer to design, build, and scale agentic LLM systems for enterprise environments. The role involves crafting tool-calling frameworks, multi-step planning, and robust back‑end services that support AI-driven workflows.

You will work with researchers and engineers to diagnose failures, optimize latency and cost, and contribute to observability and monitoring of production AI systems.

Qualifications

• 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).
• APIs, backend services, and microservices architectures.
• Cloud platforms (AWS, GCP, or Azure) and containerised systems (Docker, Kubernetes).
• Event-driven or serverless architectures familiarity.
• CI/CD pipelines, testing, and infrastructure as code.
• Debugging complex, distributed AI/ML systems.
• Experience running large-scale experiments and evaluating latency, accuracy, cost.
• Observability tools for production systems.

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.
• Build and run experiments to improve reliability, latency, cost, and success rates.
• Contribute to evaluation frameworks, observability, and monitoring of LLM/agent performance.

Skills

Python

PyTorch

TensorFlow

LangChain

LangGraph

Docker

Kubernetes

AWS

GCP

Azure

APIs

Microservices

CI/CD

Observability

Tools

Pinecone

Weaviate

OpenSearch

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 systemsDevelop RAG pipelines, embeddings workflows, and retrieval systems for enterprise dataWork with researchers and engineers to diagnose and fix failures in agent-generated code and workflowsBuild frameworks for tool-calling, multi-step planning, orchestration, and agent routingIntegrate with LLM providers (OpenAI, Anthropic, Vertex AI, open-source models) and support multi-model usageDevelop backend services and APIs to support AI-driven applications and workflowsBuild and run experiments to improve reliability, latency, cost, and success ratesContribute 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 productionStrong Python (with PyTorch, TensorFlow, or similar frameworks)Experience with agent frameworks (LangChain, LangGraph, AutoGen, or similar)Solid understanding of APIs, backend services, and microservices architecturesExperience working with cloud platforms (AWS, GCP, or Azure) and containerised systems (Docker, Kubernetes)Familiarity with event-driven or serverless architecturesExperience with CI/CD pipelines, testing, and infrastructure as codeComfortable debugging complex, distributed AI/ML systemsExperience 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 architecturesExperience optimising LLM usage across multiple providers (cost/performance trade-offs)Familiarity with vector databases (Pinecone, Weaviate, OpenSearch, etc.)Experience integrating AI systems into enterprise platforms or business workflows

Contract Details:

• £550 – £700 Per Day (Inside IR35)6 Months Initial Contract | + ExtensionsHybrid | London

Company:

Experis UK

Level of experience (years):

Senior (5+ years of experience)

Tagged as: Industry, Machine Learning, NLP, Recommendation System, United Kingdom