Technical Skillset Required :
- 9+ Years of Hands-on experience is a must have.
- Go microservices, React 19+/TypeScript, OpenShift/Kubernetes, MongoDB/Redis/S3, REST/gRPC/WebSockets, Claude/Gemini/proprietary LLMs, OAuth/JWT/Vault, GitOps CI/CD, 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 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.
(ref:hirist.tech)