- Go microservices, React 19+/TypeScript, OpenShift/Kubernetes, MongoDB/Redis/S3, REST/gRPC/WebSockets, Claude/Gemini/proprietary LLMs, OAuth/JWT/Vault, GitOps CI/CD, Prometheus/Grafana/ELK.

You might be a good fit if you :

- Bring distinguished, deep-dive software engineering expertise and a track record of architectural leadership.

- Thrive in a results-driven environment, where flexibility fuels impact and your technical decisions shape the enterprise.

- Are a game-changer and thought leader, ready to step beyond your designated role to influence the broader engineering culture.

- Love the synergy of pair programming and hands-on coding-you lead from the front and stay close to the codebase.

- Seize the opportunity to architect machine learning and GenAI applications at an unprecedented global scale.

- Possess a relentless passion to push the boundaries of machine learning and generative AI, bringing your knowledge to shape future.

What you'll do within the team :

- Engineering at scale: You will build scaled, robust services and platforms centred around generative AI. This may also include developing CLIs, SDKs, runtimes and more.

- Thought Leadership: Drive architectural vision and lead the 0-1 build of foundational, enterprise-grade AI platforms and products.

- System Design: Design and build high-quality, highly reliable, and secure distributed systems with developer and user experience at the center.

- Strategic Direction: Create "firsts" in the Generative AI space, acting as a core member of the team that defines the strategic technical direction for the entire bank.

- Scale & Iterate: Continually iterate and scale Generative AI products to handle massive throughput, whilst anticipating and listening to the complex needs of internal customers.

- Cross-Org Influence: You must be able to drive technical alignment across multiple engineering organizations, breaking down silos to deliver cohesive AI capabilities.

Experience That Will Help You Succeed In This Role :

- Mastery of Modern Stacks: Expert-level fluency in Golang and Python is a must-have, with deep experience building concurrent, high-throughput systems.

- Cloud-Native & Infrastructure: Deep expertise in the Kubernetes ecosystem, container orchestration, and modern security paradigms (e.g., Gatekeeper, zero-trust).

- Applied GenAI: Understanding of language models, embeddings models and RAG architectures is desirable

- AI Infrastructure: Proven experience designing control planes, sandboxing systems for AI experimentation, and managing large-scale vector stores and search algorithms.

- Data Engineering: Extensive experience in large-scale ETL development and data pipeline architecture.

- Security & Governance: Experience maintaining and/or contributing to bug bounty, responsible disclosure programs, and AI safety/guardrail implementations.

- Startup Agility: Experience leading technical initiatives within fast-paced startup environments or driving startup-like agility within a large enterprise.