Senior AI Engineer
Senior AI Engineer
Contract - Outside IR35 - 6 months+
c. £900/day - Oxfordshire (Hybrid 2 days a week in the office)
Our client is a rapidly scaling UK deep-tech company delivering advanced AI capability into some of the most consequence-heavy environments: defence and national security, critical national infrastructure, and enterprise clients whose decisions carry real weight. They're hiring a Senior Applied AI Engineer to take ownership of the agentic AI systems underpinning their platform, on a contract basis, with genuine influence over how those systems are architected and delivered.
This role suits an engineer who designs and ships systems rather than assembling pre-built components - someone who cares more about how a system performs once it's live and under pressure than how impressive it looks in a demo.
What You'll Be Doing
- Architecting and building multi-agent AI systems end-to-end, combining frameworks such as LangGraph or Haystack where they add value with bespoke orchestration, state management and tool-calling logic where a framework won't cut it
- Writing production-grade code with reliability, latency and graceful failure handling designed in from the start rather than bolted on afterwards
- Embedding LLMs and vision-language models into live reasoning, search, summarisation and task-execution workflows, backed by solid retrieval, memory and guardrail design
- Deploying across cloud, on-premises and fully offline/air-gapped settings, adapting your approach to each environment's security and connectivity constraints
- Taking end-to-end ownership of production pipelines, from raw data ingestion through to live inference
- Building the monitoring, evaluation and guardrail tooling that shows how a system is actually performing in the field
- Setting technical standards for agentic AI within the team, establishing the patterns other engineers follow and leaving clear documentation behind
What We're Looking For
- Robust software engineering, including developing LLM-powered or agentic systems, and a track record operating at senior/lead level
- Strong engineering fundamentals - code that's clean, tested and built to last, not just prototypes that work once
- Commercial track record building and owning multi-agent or agentic AI systems in live production settings, as an engineer rather than an integrator
- Strong Python skills, comfortable working with LangGraph, LangChain, Haystack or similar, and equally comfortable dropping below the framework when that's the right call
- Real-world experience deploying AI/ML systems into production, beyond notebooks and proof-of-concepts
- Confidence across inference performance, data pipeline design, state/memory handling, and tool or function calling
- Experience building retrieval and search over very large, multi-modal datasets (multi-terabyte scale, spanning text, imagery, telemetry and sensor feeds), including indexing and embedding at scale
- Comfortable with Docker, Git and cloud infrastructure, ideally AWS
- Understanding of secure deployment approaches: air-gapped, on-premises or sovereign cloud
Nice to Have
- Multimodal reasoning and/or edge or offline AI deployment experience
- Kubernetes experience (EKS or OpenShift)
- MLOps background: evaluation, monitoring, reproducibility
- Observability for agentic systems, covering drift, agent behaviour and performance
- Familiarity with agent-to-agent orchestration protocols or the Model Context Protocol (MCP)
- Awareness of secure-by-design frameworks (ISO 27001, NIST, OWASP)
- Background in defence, national security or other regulated sectors
- Open-source AI/ML contributions
Why Apply
- Real technical ownership: shape the architecture, not just work through a backlog
- Work at the leading edge of agentic and generative AI, on systems people genuinely depend on
- Join a fast-scaling business with a strong chance of the contract extending or evolving further
- Flexible, hybrid working arrangement
- Strong day rate reflecting seniority and scope
This is a contract engagement operating outside IR35, offered on an initial 6-month term with a strong likelihood of extension.
Keywords: Applied AI Engineer, AI Engineer, Machine Learning Engineer, LLM Engineer, Agentic AI, Multi-Agent Systems, LangGraph, LangChain, Haystack, Python, RAG, Retrieval Augmented Generation, NLP, AWS, Docker, Kubernetes, MLOps
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