Software Engineer

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