Staff Software Engineer

Staff Software Engineer (AI)

You are a hands on engineer who thrives on solving complex problems with clean, reliable code.

We are a growing team within the bank and constantly involved in industry changing solutions.

Together we will build tomorrow's bank today, using world leading engineering, technology, and innovation.

Do work that matters

Join the Operational Risk & Compliance Crew to engineer our core AI enabled risk platforms. Your focus is hands on, high quality software engineering across .NET and Python on AWS building secure APIs and microservices, contributing to CI/CD pipelines, and improving resilience and observability. You will work within a squad delivering agentic AI capabilities into risk management processes that operate across the bank. Gen AI is a core enabler of the solutions you'll build. Data is a supporting concern, primarily consuming producer led data products and event streams.

See yourself in our team

Risk Management is modernising how the bank identifies, assesses, and manages risk building an enterprise grade Risk AI Platform powered by an AWS first approach, ArgoCD managed deployments, and strong API standards. The platform underpins a growing portfolio of AI enabled products that automate risk processes, embed agentic intelligence, and deliver scalable, human in the loop workflows across Operational Risk & Compliance.

You will collaborate with Product Owners, Data Scientists, Principal Engineers, Risk Technology, and adjacent crews to deliver platform capabilities, extend AI driven features, reduce toil, and meet tech control and privacy obligations. You'll be a key technical contributor within your squad delivering production quality code, participating in design decisions, and helping uplift the engineers around you.

Key Responsibilities

• Design, build, and operate .NET/Python microservices and REST APIs with OpenAPI specs and Kong gateway integration as part of the Risk AI Platform.
• Deliver production quality code across the full stack backend services, API layers, and frontend components with a focus on reliability, testability, and maintainability.
• Contribute to architectural decisions : participate in design reviews, propose solutions for technical challenges, and support the Principal Engineer in driving refactors, modularisation, and performance improvements.
• Build and maintain CI/CD pipelines (GitHub Actions + ArgoCD), automated tests (unit, integration, performance), and progressive delivery workflows.
• Implement observability and operability (Grafana, Prometheus, PagerDuty) including dashboards, alerting, and SLO/SLI instrumentation.
• Build agentic AI features : develop and extend multi agent workflows, conversational AI components, and Rules as Code integrations that power intelligent risk assessments.
• Work with LLM APIs/platforms, agent frameworks (e.g. LangGraph) , and evaluation tooling to deliver reliable, observable AI capabilities.
• Partner with product and platform teams to estimate, plan, and deliver increments that produce measurable outcomes for risk operations.
• Apply secure coding practices in line with Tech Controls and Privacy Front Door processes, including secrets management, encryption, and access control.
• Consume producer led data products (S3/Iceberg, Kafka, DynamoDB) as inputs to platform features; maintain clean integration boundaries.

We're interested in hearing from people who

• Are curious, life long learners who stay across emerging AI and engineering practices.
• Can influence the future of the company's technology estate every day.
• Can create a culture focused on accelerating the adoption of new and emerging technologies.
• Want to grow into technical leadership, you're looking for a role where you can deepen your craft while expanding your influence.
• Are passionate about using AI to solve real world problems in risk management and governance.

Technical Skills

• Strong software engineering skills in .NET and/or Python, with experience building and operating production microservices and APIs. Familiarity with FastAPI and REST/OpenAPI contract design is a plus.
• Exposure to AI and agent engineering : Experience with or strong interest in agent orchestration frameworks (e.g. LangGraph), LLM API integration (e.g. LiteLLM), prompt engineering, and AI observability tooling (e.g. Langfuse, HoneyHive). You're eager to deepen your skills in building reliable AI systems.
• Frontend development experience: Working knowledge of React, Next.js, and Node.js to contribute to responsive, production grade user interfaces and backend for frontend layers.
• Solid AWS cloud experience: H ands on with core services such as EKS (Kubernetes), DynamoDB, S3, CloudFormation, and ALB/EC2.
• CI/CD and containerisation experience: GitHub Actions, ArgoCD, Dock