BAE Systems
AI/ML Engineer
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AI/ML Engineer
Location: UK Wide. We offer a range of hybrid and flexible working arrangements. Please speak to your recruiter about the options for this particular role.
Salary: Competitive, depending on experience
Who we are:
Join BAE Systems and you’ll be part of something bigger. As a valued member of our global colleague network, you’ll bring your unique skills and perspectives to help pioneer progress and protect what matters most. You’ll be trusted to play your part in delivering the advanced, technology-led defence, aerospace and security solutions of tomorrow, shaping a safer future, for all of us.
From the depths of the ocean, to the far reaches of space, there’s no limit to where a career at BAE Systems could take you.
Job Description:
We are seeking a Senior AI & ML Engineer to design, build and support production-grade AI solutions that deliver measurable business value. You will develop and deploy large language model (LLM) applications end-to-end, including retrieval logic, prompt engineering, orchestration workflows and supporting APIs.
Working closely with data scientists, engineers and business stakeholders, you will implement Retrieval-Augmented Generation (RAG) solutions, optimise data retrieval strategies and ensure secure access controls are enforced. You will define and maintain frameworks for evaluating answer quality, monitor model performance and drive continuous improvement through testing and governance.
The role includes taking experimental AI solutions into production, ensuring code quality, reproducibility and operational resilience. You will manage model and prompt lifecycles through MLflow, oversee model promotion and rollback processes, and deploy AI services to Azure and OpenShift using GitLab CI/CD pipelines.
You will also monitor live services for quality, drift, latency and cost, helping shape and evolve the organisation's AI ecosystem.
Core duties:
- Build and run production LLM applications end to end, from use case design through to live service – retrieval logic, prompt design, orchestration and the APIs behind them
- Design and implement RAG solutions, including chunking and embedding strategy, vector indexing and retrieval filtering that enforces user entitlements at the data layer
- Establish how answer quality is measured – define evaluation sets, baseline performance before release and re-evaluate after any change to prompt, model or document set
- Take experimental work from data scientists into production, including code review, refactoring for modularity, dependency handling and making it reproducible
- Own the model and prompt lifecycle in MLflow – tracking, registry, versioning, promotion and rollback. Ensure training and inference remain consistent
- Execute promotion of models and use cases into production serving, against a governance approved admission policy
- Deploy AI inference services into OpenShift and Azure with CI/CD pipeline in GitLab, comprehensive monitoring, logging and alerting, and secrets management
- Monitor live AI services into OpenShift and Azure for answer quality, drift, latency and cost, investigate regressions and trace cost increases to their cause
- Work with data scientists, data engineers, platform engineers and business stakeholders to industrialise AI use cases, and support the evolution of the AI ecosystem
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Your Skills and Experience:
- Demonstrable experience developing, deploying and operating machine learning and AI solutions in production environments, not proof of concept
- Hands on experience building LLM applications, including RAG, in Python with frameworks such as LangChain. Demonstrate a working understanding of why RAG solutions underperform and how to fix them
- Practical experience of vector databases and embeddings, such as Qdrant or Azure AI Search, and evaluating retrieval quality rather than assessing it by inspection
- Experience of monitoring live AI services – answer quality, drift, latency and cost – including attributing inference cost to use cases and tracing increases back to prompt or model change, using ai monitoring and inference gateway tooling
- Proven knowledge of Kubernetes or OpenShift and containerised deployment, with CI/CD in Gitlab or equivalent, secrets management, and monitoring with Prometheus, Grafana and Loki
- Experience implementing governance and guardrails for AI services in a regulated or security conscious environment 0 model admission and provenance, responsible AI controls and auditable of what was deployed and why
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The Data and Analytics team:
This is an opportunity to join a new part of the business, undertaking a new piece of work, introducing new technology into the wider BAE Business. Joining from the ground up, this is a chance to make your mark and the role your own. This role will provide the opportunity to grow the role & your responsibility into a wider scope or even specialise within a specific area.
Why BAE Systems?
Here you’ll build a career with purpose and limitless possibilities. With lifelong learning and meaningful work, this is a place where you can grow your career with confidence and be empowered to be your best. You’ll be recognised for your contribution and enjoy rewards tailored to what’s most important to you and your family, support for your financial and personal wellbeing, as well as a balanced lifestyle. In an environment embracing sustainable ways of working and with a strong sense of shared purpose, our supportive culture is a place you can feel you belong and proud of the difference you make.
A place where everyone can thrive:
We’re committed to building an inclusive workplace where everyone feels valued and supported. We know that a diversity of backgrounds, perspectives and experiences strengthens our teams and is vital to the work we do.
Please be aware that many roles at BAE Systems are subject to both security and export control restrictions. These restrictions mean that factors such as your nationality, any nationalities you may have previously held, and your place of birth can restrict the roles you are eligible to perform within the organisation. All applicants must as a minimum achieve Baseline Personnel Security Standard. Many roles also require higher levels of National Security Vetting where applicants must typically have 5 to 10 years of continuous residency in the UK depending on the vetting level required for the role, to allow for meaningful security vetting checks.
Closing Date: 6th October 2026
We reserve the right to close this vacancy early if we receive sufficient applications for the role. Therefore, if you are interested, please submit your application as early as possible.
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