Architect and lead the implementation of production-grade AI solutions leveraging LLMs, transformer-based models, RAG pipelines, and agentic systems.
Design, develop, and optimize multi-step AI agents capable of tool/API invocation, reasoning chains, and state management.
Oversee the deployment of AI-powered applications across cloud environments (AWS, Azure, or GCP) ensuring scalability, reliability, and cost-efficiency.
Establish best practices for prompt engineering, evaluation frameworks, and model performance monitoring (latency, grounding, factuality, cost).
Implement guardrails and Responsible AI practices, including prompt injection mitigation, content moderation, bias reduction, and safety controls.
Collaborate cross-functionally with Data Scientists, Software Engineers, and Product stakeholders to take AI solutions from prototype to full production ownership.
Mentor and guide junior and mid-level engineers, ensuring high-quality, modular, and maintainable Python code standards.
Drive experimentation strategies, define KPIs, and promote data-driven decision-making across AI initiatives.