AI Engineer

Must hold SC or DV Clearance

Experience, qualification, and soft skills, have you got everything required to succeed in this opportunity Find out below.
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 xwzovoh 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