Job Description:

OXFIDA (formerly Aioi R&D Lab – Oxford) is an AI R&D company based in Oxford, on a mission to harness AI to understand, predict, and manage risk, helping build a safer, more resilient society. 

We sit at the intersection of academia and industry, working with Oxford's professors and researchers alongside commercial partners, and combining that expertise with real-world risk data at global scale to turn frontier research into AI that actually ships rather than just gets published. 

Our work spans AI for insurance underwriting and claims, AI risk governance, privacy-preserving technologies for agentic AI, and quantum optimisation, alongside partnership projects on nature and supply chains and the emerging challenges nobody's solved yet. 

We build AI products and solutions for insurers, businesses, and public-sector organisations worldwide, and run innovative research projects that push these technologies further, helping people make better decisions in an uncertain world. 

See risk clearly. 

Contract: 18-month fixed-term contract from signing, running until the end of February 2028 ·

Location: Hybrid or Remote

The role 

You'll join a small, technically strong delivery team, helping to take our AI Risk Governance product from pilot through to production or within our Pricing Engine Product which is a live and deployed product used by many. There’ll also be opportunities to contribute to our broader project portfolio, building the software and infrastructure that turns research and product ideas into things that actually run. It's a senior, hands-on engineering role with scope to learn, grow and put things in the hands of real users. 

Why join us 

• A senior, genuinely hands-on engineering role, not one that quietly turns into pure management. 

• Broad exposure across OXFIDA's project portfolio, from the Pricing Engine to fraud detection and AI risk governance, rather than being tied to a single narrow codebase. 

• We have strong ambitions in the AI Risk space and you would get to join at the early stages of developing our products in this area.  

Responsibilities

What you'll do 

• Contribute directly to the development, testing, and maintenance of OXFIDA projects, products, and initiatives. 

• Build robust, maintainable, and operationally sound software and infrastructure using our core stack: React, TypeScript, Material UI, Node.js, Python, PostgreSQL, Docker, Kubernetes, Helm, and AWS. 

• Work with ML engineers, ML scientists, product managers, and external project partners to understand technical requirements, constraints, and delivery priorities. 

• Support other engineers through code review, pair programming, and mentoring, and champion engineering best practice across OXFIDA. 

• Troubleshoot technical, data, and integration issues arising during development and deployment. 

• Drive improvements to internal tooling, engineering standards, reusable frameworks, and deployment practices across OXFIDA. 

• Communicate technical trade-offs, risks, and progress clearly to both technical and non-technical stakeholders. 

Knowledge, Experience and Qualifications

What you'll bring 

• 5+ years of commercial software experience. 

• A degree in Computer Science, Mathematics, Statistics, Physics, Engineering, or another relevant STEM discipline, or equivalent practical experience. 

• Familiarity with our core stack, with strong experience in at least two of: Python, TypeScript, relational databases, APIs, Docker, Kubernetes, Kubeflow, AWS. 

• Strong core software engineering and DevOps skills, including CI/CD, version control, containerisation, and cloud deployment. 

• A solid grasp of engineering best practice, producing clean, maintainable, well-tested code. 

• Comfort with code review, giving clear, actionable, constructive feedback to others. 

• Proven effectiveness in a remote-first, iterative agile environment. 

• Experience working across the full lifecycle, from experimentation and prototyping through to integration and operationalisation. 

• Ability to work effectively in technically complex, ambiguous environments involving multiple stakeholders. 

• Strong communication skills, including explaining technical issues and trade-offs clearly to non-specialists. 

Bonus points: experience architecting complex distributed software systems for cloud environments, experience deploying ML, AI, or data-driven systems into production or near-production settings.