Description
This is not a traditional assurance role. You will work directly with engineers and leadership to challenge how critical systems are designed, built and delivered, focusing on the risks that matter.
You will operate across a wide range of projects, from low-latency platforms to large-scale data systems. You will build a deep understanding of how things work and where they can fail, asking the right questions and providing clear, evidence-based insight to improve outcomes.
The role suits someone with strong technical curiosity and commercial awareness. You will be comfortable diving into complex systems and delivery mechanics while also assessing how they support strategic goals.
Key responsibilities of the role include:
- Analysing system architecture, interactions and alignment with overall strategy
- Deep diving into areas like CI/CD, resilience, availability and APIs
- Working with engineers to map systems, data flows and dependencies
- Using data, modern tooling and AI-assisted analysis to spot patterns, weaknesses and emerging risks early
- Evaluating how work is structured, prioritised and executed across teams
- Assessing how goals translate into real delivery on the ground
- Identifying gaps at system boundaries, integrations and third-party touchpoints
- Reviewing performance metrics ensuring they reflect real outcomes
- Using AI tools to synthesise complex technical information, identify non-obvious risks and improve the quality and speed of insights
- Breaking down complex systems and issues into simple, useful insights
- Sharing findings with senior engineers and leadership to influence decisions
- Highlighting opportunities to improve systems, delivery and strategy
- Contributing to a modern, technology-focused approach to risk assessment
Ideal skills and experience:
- Interest in using AI and data to analyse complex systems, surface non-obvious risks and enhance decision-making
- Enjoy moving between technical detail and big-picture thinking, and are naturally curious about how systems, teams and technologies actually work
- Experience in engineering or technology risk, with knowledge of modern practices such as Agile, DevOps, CI/CD and distributed systems
- Ability to form clear, practical views in ambiguous situations, balancing technical and commercial considerations
- Strong communication skills with ability to influence through insight and credibility
- Strong academic background, ideally in Computer Science, Engineering or a related analytical field