Lead Agentic AI Delivery at Enterprise Scale
- Lead end-to-end architecture, design, and production deployment of Agentic AI solutions for complex enterprise and Life Sciences use cases
- Build, deploy, and optimize multi-agent systems involving planning, reasoning, orchestration, tool usage, and memory management
- Drive GenAI implementations beyond POCs into stable, scalable, and observable production systems
Deep Integration with Enterprise Data Platforms
- Architect and integrate Agentic AI systems with Databricks, data lakes, data warehouses, streaming platforms, and enterprise APIs
- Design and optimize scalable ETL / ELT pipelines (batch and streaming) to power AI, ML, and GenAI workflows
- Ensure data quality, lineage, freshness, and governance for AI-driven applications
AI Architecture, Optimization & Governance
- Define architecture patterns, guardrails, and governance frameworks for enterprise Agentic AI
- Optimize agent workflows through prompt engineering, tool selection, orchestration strategies, and memory design
- Define approaches for context management, token efficiency, latency optimization, and cost control
- Ensure reliability, observability, security, and performance of AI systems in production
Leadership & Stakeholder Engagement
- Partner with business stakeholders to identify high-impact AI use cases and translate them into scalable solutions
- Mentor and lead cross-functional teams across Data Engineering, AI/ML, and Application Engineering
- Participate in client discussions, roadmap definition, solutioning, proposals, and Agentic AI thought leadership
