Technical Architect

Our client is building a new AI capability for a live operational environment and needs a Solution Architect to take ownership of it end to end - from how models are trained, through to inference, through to how it all knits into an existing technical estate. You’d be the technical anchor point on this: the person suppliers and engineering teams turn to when a design decision needs making, and the person accountable for holding that architecture steady as delivery moves forward.

What the role actually involves

This is a build-and-defend role. You’ll shape the architecture, write it up properly (HLDs, LLDs, decision records, options papers with real costed trade-offs), and then stand behind it in front of design authority and assurance boards when it gets challenged.

It’s a genuinely technical AI role rather than a strategic overview one - you’ll need to know, in practice, how model serving actually works at scale, where inference bottlenecks show up, and how the levers between accuracy, latency and cost actually trade off against each other. You should also be comfortable enough with computer vision (CNNs, vision transformers, detection and segmentation methods) to push back on a data science team’s approach when needed.

Day to day, you’d be:

• Taking ownership of the model lifecycle - pipelines, registry, versioning, CI/CD, drift detection, and retraining logic
• Working out how to run models in constrained or edge settings: quantisation, pruning, distillation, ONNX/TensorRT, and picking the right accelerators for the job
• Setting the evaluation approach - where precision and recall trade off, where thresholds sit, and how much false-positive friction is acceptable for the people using the system
• Designing so the model supports human decision-making rather than overrides it
• Building for sites with poor or intermittent connectivity, with training centralised and models pushed out from there
• Getting the non-functional side right at scale - throughput, latency, availability, resilience, DR - across multiple sites
• Reviewing and challenging supplier architecture, including calling out vendor lock-in risk and build-vs-buy calls
• Working to Secure by Design principles and NCSC guidance throughout, given the OFFICIAL-SENSITIVE classification

• A track record as a solution/technical architect on AI projects sitting inside bigger strategic programmes
• Solid AWS experience - S3, Lambda, EventBridge, SNS/SQS
• Comfortable working across TOGAF, ArchiMate, C4, UML and BPMN
• Hands-on with MLOps tooling and platforms - SageMaker, OpenVINO or equivalent
• Experience architecting data for large volumes of imagery - tiering, retention, lineage, provenance
• Familiar with the governance side of AI - DPIAs, model documentation, bias and fairness checks
• Strong stakeholder handling, and the ability to explain architecture to people who aren’t architects
• This role requires active SC Clearance
• Background in X-ray-based AI models or density/object identification
• Public sector delivery experience - GDS standards, Technology Code of Practice, spend controls
• Knowledge of the DSIT AI Playbook or the Algorithmic Transparency Recording Standard
• FinOps experience specifically around GPU and inference cost
• Experience integrating with scanner/hardware OEM systems and real-time image pipelines