Key Responsibilities :

AI System Development :

- Design and build Agentic AI workflows using modern LLM orchestration frameworks.

- Develop intelligent systems that combine LLM reasoning, structured workflows, and external tools or APIs.

- Implement production-grade AI products using Python-based backend frameworks.

- Integrate LLM/SLM models into enterprise applications with strong reliability and performance considerations.

Architecture & Technical Leadership :

- Own the technical architecture for AI systems and ensure alignment with scalability, security, and maintainability best practices.

- Lead technical design discussions and guide engineering teams on system architecture and implementation decisions.

- Establish standards for code quality, modularity, testing, and deployment.

- Build and manage systems using modern LLM orchestration and observability frameworks.

- Implement evaluation, monitoring, and debugging workflows for LLM-based systems.

Technical Delivery Ownership :

- Take ownership of technical delivery across AI projects, ensuring solutions are robust, maintainable, and aligned with business objectives.

- Work closely with product, data science, & engineering teams to translate requirements into scalable technical implementations.

- Identify potential technical risks and proactively propose solutions or architectural improvements.