Derived from job-description analysis by Serendipath's career intelligence engine.
Original posting from Experis UK
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
- Comfortable debugging
complex, distributed AI/ML systems
- 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
- Experience 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:
- £600 - £700 Per Day (Inside IR35)
- 6 Months Initial Contract | + Extensions
- Hybrid | London
Please apply for immediate consideration.
Source: Experis UK careers