Principal Software Engineer

• You are a problem solver with a strong background in software engineering

• 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

As the Technical Lead within the Consumer Underwriting Crew, you will lead engineering for our AI-enabled decisioning platforms. Your primary focus is hands-on, modern and reliable software engineering across .NET and Python on AWS, building secure APIs and microservices, AI driven agentic workflows, uplifting CI/CD, and improving resilience and observability. You will drive the technical direction as we scale these platforms from MVP to enterprise-grade capability, embedding agentic AI into risk management processes that operate across the bank. Gen AI is a core enabler of the solutions you'll build.

See yourself in our team

In Consumer Underwriting, we help our customers get access to our banking products to meet their lending needs. We are redefining how customers interact with us by providing a seamless digital application process, as we build enterprise-grade AI Platforms. With an ambition to provide the best lending experience, we have a clear strategy to unlock the best experience for our customers using Agentic AI systems sitting on top of our Data assets.

We’re interested in hearing from people who can

• Own engineering for Tech assets: design, build, and operate .NET/Python microservices and REST APIs with OpenAPI specs and Kong gateway integration

• Transform ideas to enterprise solutions: drive architectural decisions, modularisation, performance tuning, and reliability improvements as we bring cutting edge innovations to life

• Provide hands-on technical leadership: write production code, conduct peer reviews, define engineering standards, and guide Staff and Senior engineers in solution design and delivery

• Establish golden paths for CI/CD (GitHub Actions), automated testing (unit, integration, performance), and progressive delivery

• Embed observability and operability (Grafana, Prometheus, PagerDuty) with SLOs/SLIs and production readiness reviews

• Drive the integration of agentic AI capabilities: build and extend multi-agent architectures, conversational AI workflows, and Rules-as-Code frameworks that power intelligent risk assessments

• Apply knowledge of LLM APIs/platforms, agent frameworks (MCP, A2A), and planning/optimisation patterns to strengthen solution architecture and interoperability across the Risk AI ecosystem

• Partner with Product Owners, Data Scientists, and platform teams to plan increments, de-risk changes, and deliver measurable outcomes for risk operations

• Ensure compliance with Tech Controls and Privacy Front Door processes; champion secure coding, secrets management (SSO/RBAC, SailPoint), and encryption

• Consume producer-led data products (S3/Iceberg, Kafka) as inputs to platform features; avoid tight coupling to data storage layers

Technical Skills:

We use a broad range of tools, languages, and frameworks. We don’t expect you to know them all but experience or exposure with some of these (or equivalents) will set you up for success in this team;

• Deep software engineering expertise in .NET and/or Python, with a track record of building and operating production microservices and APIs at scale. Experience with FastAPI and REST/OpenAPI contract design is highly valued.

• AI and agentic engineering experience particularly with agent orchestration frameworks (e.g. LangGraph), LLM gateway/proxy patterns (e.g. LiteLLM, Portkey), prompt engineering, and AI evaluation/observability tooling (e.g. Langfuse, HoneyHive). You don't need to be a data scientist, but you understand how to engineer reliable, observable AI systems.

• Modern frontend capability: experience with React, Next.js, and Node.js to build responsive, production-grade user interfaces and backend-for-frontend layers.

• Strong AWS cloud experience: Hands-on with ECS, Postgres, DynamoDB, DocumentDB, S3, CloudFormation, ALB, and EC2. You're comfortable designing for high availability across multiple availability zones. Design with Finops view.

• Hands-on CI/CD and GitOps experience: GitHub Actions, containerisation (Docker, Helm/Kustomize), and automated testing strategies across unit, integration, and performance layers. Familiarity with testing automation tools like Specmatic

• Observability and operational excellence: Experience building dashboards and alerting with Grafana, Prometheus, CloudWatch, and ELK/Obstack, backed by SLOs/SLIs and production readiness reviews. Familiarity with PagerDuty for incident management.

• A security-first mindset: familiarity with enterprise identity and access management (PingSSO/OIDC, SailPoint for RBAC), AWS Secrets Manager, and secure coding practices within a regulated environment.

• Data literacy: Experience working with event streams (Kafka), cloud-native data formats (S3/Iceberg), AWS services like Lake formation, EMR, understanding of Semantic Data modelling as a consumer of producer-led data products.

• Strong architectural thinking: you can modularise a codebase, design API contracts, define integration patterns, and make pragmatic trade-offs between speed and sustainability.

Working with us:

We support our people with the flexibility to balance where work is done with at least half their time each month connecting in office. We also have many other flexible working options available including changing start and finish times, part-time arrangements and job share to name a few. Talk to us about how these arrangements might work in the role you’re interested in.

If this sounds like the role for you then we would love to hear from you. Apply today!