Your Responsibilities
- Shape the AI/ML architecture, technology stack, and engineering standards of the unit
- Design, build, and operate production-grade AI and machine learning systems and own their reliability, quality, latency, and cost
- Develop classical ML and GenAI solutions, including RAG, agentic systems, and AI-powered services
- Productionize ML models developed by our Data Scientists and operate them at scale
- Define and enhance MLOps and LLMOps practices for deployment, versioning, monitoring, evaluation, and retraining
- Own our LLM gateway, including model routing, token limits, cost per use case, guardrails, and logging
- Build scalable AI services and APIs for our Full-Stack and AI Deployment Engineers
- Evaluate emerging AI models, AI tooling, and agentic systems and integrate impactful innovations into our stack
- Share knowledge and support the growth of junior colleagues – this is a senior individual contributor role
