To design and scale our production-grade AI systems—from LLM-powered applications and agentic workflows to the data and MLOps foundations behind them. The candidate will own architecture decisions end to end and translate business problems into deployable, reliable AI solutions.
Candidate must have:
Experience:
- 5+ years in AI/ML or software engineering, with hands-on architecture experience
- Architect modular, maintainable, and high-performance backend systems.
- Lead and mentor a team of Python developers and ML engineers
- Build and optimize AI/ML models for real-world business problems
- Own the backend lifecycle: design → development → testing → deployment.
- Build and scale RESTful APIs, microservices, and data pipelines.
Programming & Framework:
- Strong Python and agentic frameworks (LangChain, LangGraph, or similar)
AI/LLM Expertise:
- Deep understanding of LLMs, RAG, embeddings, and vector databases
Cloud & Ops:
- Cloud-native experience (Preferably AWS) and MLOps
Architecture:
- Ability to design scalable AI/GenAI architectures, agentic and RAG-based systems, and define data governance and security practices
Stakeholder Management:
- Excellent communication and stakeholder-influencing skills; able to turn business needs into technical roadmaps