Join us as a Software Engineer
- This is an opportunity for a driven Software Engineer to build AI-enabled products and workflows that solve real business problems
- You'll engineer reliable, scalable software and automation that connects modern AI capabilities with real-world risk and control processes
- We're offering this role at associate level
What you'll do
In your new role, you'll be working within a feature team to engineer software, scripts and tools, as well as liaising with other engineers, architects and business analysts across the platform.
You'll Also Be
- Engineer and ship AI-enabled software, services and automation that support and enhance controls and governance processes
- Integrate LLM capabilities, retrieval patterns and API-based services into products and internal workflows in a secure, maintainable way
- Build, test, deploy and support backend services, scripts and lightweight web components across the full software lifecycle
- Design and improve orchestration for multi-step workflows, event-driven processes and cross-system integrations
- Evaluate solution quality across accuracy, reliability, latency and cost, and refine implementations using testing, monitoring and structured feedback
- Collaborate with engineers and business stakeholders to turn ambiguous requirements into clear, scalable technical solutions aligned to control's strategy
- Improve automation, resilience and engineering quality through reusable components, better tooling and disciplined delivery practices
The skills you'll need
To take on this role, you'll need a background in software engineering, software design, and architecture, and an understanding of how your area of expertise supports our customers.
You'll Also Need
- Strong software engineering foundations like clean, testable code,Git,debugging, basic CI/CD, solid Python for backend/AI integration, JavaScript/TypeScript for web,and good SQL/data handling
- Designing or consuming REST and GraphQL APIs; LLM integration (prompts, configuration, evaluation); retrieval-augmented generation, embeddings, vector databases; workflow/orchestration; and event-driven architectures (queues, webhooks, pub/sub)
- Secure, scalable systems experience: authentication and integration patterns (OAuth, API keys, service accounts, schema transformation); familiarity with cloud and enterprise platforms (managed AI, serverless, business systems); and focus on data pipelines, quality, latency, accuracy and cost
- Strong communication and stakeholder skills, with the ability to turn business needs into technical solutions and explain trade-offs clearly. Curiosity and adaptability in a fast-changing AI landscape, with the judgement to evaluate new tools quickly and avoid over-reliance on any single stack
- Experience or awareness of risk, controls frameworks or enterprise risk management (e.g. EWRMF) is beneficial but not essential
