Technical Architect

Venturi; Greater London; On-site; GBP 90,000 - 130,000; Full time

Job summary

Venturi is seeking an experienced Solution Architect to own a new AI capability end-to-end in a predominantly remote setting with occasional travel to South London. You will define data, model lifecycle and deployment strategies, balancing accuracy, latency and cost while aligning with existing tech estate.

The role demands hands-on experience with MLOps, AWS (S3, Lambda, EventBridge, SNS/SQS), and governance practices, including DPIAs and transparency standards, with focus on imaging data and

Qualifications

• Experience as solution/technical architect on AI projects within large programmes.
• Hands-on with AWS services and MLOps tooling (SageMaker/OpenVINO).
• Familiar with TOGAF/ArchiMate/C4/UML/BPMN frameworks.
• Knowledge of AI governance, DPIAs, bias checks and AI Playbooks.

Responsibilities

• Take ownership of the model lifecycle: pipelines, registry, versioning, CI/CD, drift detection.
• Design for constrained/edge environments with quantisation and ONNX/TensorRT.
• Define evaluation approaches balancing precision, recall and thresholds.
• Ensure architecture supports human decision-making and safety.
• Collaborate with vendors and ensure security by design and NCSC guidance.
• Work on sites with poor connectivity and multi-site resilience requirements.
• Review supplier architectures and flag build-vs-buy risks.
• Lead cross-functional stakeholders and translate architectures for non-architects.

Skills

AI architecture

Stakeholder communication

Data architecture for imagery

AI governance

Security clearance

X-ray image AI

Public sector delivery

AI governance standards

FinOps for AI

Image pipelines integration

AI model lifecycle

Edge deployment

Cost vs latency trade-offs

Model evaluation design

Tools

AWS

TOGAF

ArchiMate

C4 model

UML

BPMN

SageMaker

OpenVINO

Job description

Location: Predominantly remote (Occasional travel to South London)

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

What you'll bring

• 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