Senior Applied AI Engineer

Deerfoot IT Resources Limited; East Hagbourne; Hybrid; GBP 129.000 - 166.000; Vollzeit

Zusammenfassung

Deerfoot IT Resources Limited seeks a Senior Applied AI Engineer to own and deliver multi-agent AI systems on a contract basis outside IR35. The role is based in Oxfordshire with a hybrid pattern (2 days on site per week) and a day rate of £700-£900.

The project focuses on deploying robust AI capabilities in biotech/pharma contexts and requires leading-edge architectural ownership. You will architect end-to-end agentic AI systems, embed LLMs and multi-modal models, optimize performance, and

Qualifikationen

• Strong background in building production-grade AI systems.
• Experience shipping multi-agent or agentic AI in live environments.
• Proficient in Python and cloud-based deployment (AWS preferred).
• Hands-on with LLMs, retrieval, memory and guardrails.

Aufgaben

• Architect end-to-end multi-agent AI systems for live use.
• Write reliable production-grade code with performance and fault-tolerance.
• Embed LLM/vision-language models into live reasoning pipelines.
• Deploy across cloud and on-prem environments with security in mind.
• Own production pipelines from raw data to live inference.
• Build monitoring and guardrail tooling to measure real-world performance.
• Set engineering standards and create clear documentation.

Kenntnisse

Python

LLM deployment

Multi-agent systems

Production-grade software

System design

Data pipelines

Secure deployment

Inference performance

Tools

Docker

Git

AWS

Kubernetes

OpenShift

LangGraph

LangChain

Haystack

Jobbeschreibung

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 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, 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 cloud

Nice 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 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
• 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.