Software Engineer

Job description

Job Description - -------------- 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