Must hold SC or DV Clearance

Permanent (may consider Contractors) You will work closely with the entire team. You will be trusted with judgment calls. You will influence the business. And you will see the impact of your work every day.

If you are excited by ownership, pace and purpose - and by building something that genuinely matters - we would love to hear from you.

What You Will Be Doing

We are looking for AI engineers who build and ship agentic AI systems in production. You will work at the cutting edge of agentic and generative AI - designing multi-agent pipelines, integrating large language models and vision-language models into real workflows, and deploying them into secure and air-gapped environments for defence and national security customers.

This is a delivery role. You will own features end-to-end - from design through to deployment in constrained environments where reliability and security matter more than speed to market.

Key Responsibilities

Architect, build, and optimise multi-agent AI systems using frameworks such as LangGraph, Haystack, or equivalent

Integrate LLMs and vision-language models into agent workflows for reasoning, search, summarisation, and task execution

Deploy AI systems into cloud, on-premises, and air-gapped environments

Build production-ready pipelines from data ingestion through to inference

Experience with observability for AI systems, including agent behaviour, model performance, and failure modes

Collaborate with engineers, product leads, and customers to translate requirements into working systems

Contribute to evaluation frameworks, system integration, and performance tracking

Act as a technical authority for agentic AI - setting design patterns for junior engineers

Requirements Required

Active SC clearance

Commercial experience building multi-agent or agentic AI systems in production

Strong Python skills and hands-on experience with LLM frameworks (LangGraph, LangChain, Haystack, or similar)

Experience deploying AI/ML systems into production environments

Familiarity with Docker, Git, and cloud platforms (AWS preferred)

Understanding of secure deployment patterns - air-gapped, on-premises, or sovereign cloud

Preferred

Experience with multimodal reasoning

Experience with edge or offline AI deployments

Familiarity with Kubernetes (EKS/OpenShift) for monitoring and managing deployed applications

MLOps experience - model evaluation, monitoring, reproducibility

Observability tooling for agentic systems (model drift, agent behaviour, performance monitoring)

Experience with agent orchestration patterns and inter-agent communication protocols (e.g. A2A)

Familiarity with MCPs for tool and context integration in agentic systems

Familiarity with secure-by-design development principles (ISO 27001, NIST, OWASP)

Experience in defence, national security, or similarly regulated environments

Contributions to open-source AI/ML projects

Soft Skills

Delivery-focused - you ship working systems, not prototypes

Comfortable operating across the stack when needed

Strong communicator - can present to technical and non-technical stakeholders

Thrives in small teams with high ownership

Benefits include:

Rapid career progression and personal growth

Flexible working hours

Opportunity to shape the future of a fast-growing business

Hybrid working model

Company pension (NEST) with 4% employer contribution

Private Healthcare

29 days holiday + public holidays

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