Senior Applied AI Engineer

Senior Applied AI Engineer Contract

Outside IR35 £700 - £900 per day DOE

6 months + likely extension

Oxfordshire (hybrid - 2 days p/w on site)

Our client is a rapidly scaling UK deep-tech company delivering advanced agentic AI capability. This role sits in their AI team, working with a commercial customer in biotech and pharma. They are 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 and on-premises environments, 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 behindWhat 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, including indexing and embedding at scale

Comfortable with Docker, Git and cloud infrastructure, ideally AWS

Understanding of secure deployment approaches, including on-premises and sovereign cloudNice to Have

Biotech, pharma or life sciences domain experience

Multimodal reasoning 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)

Open-source AI/ML contributionsWhy 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

Strong day rate reflecting seniority and scopeThis is a contract engagement operating outside IR35, offered on an initial 6-month term with a strong likelihood of extension.

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