• Build and orchestrate LLM agents using Gemini Pro and LangChain • Design, implement, and operate RAG solutions at scale • Integrate with Gemini and Vertex AI services using API-driven architectures • Debug and optimize end-to-end LLM pipelines, including: chunking strategies, embeddings, retrieval logic, LLM response behavior • Deliver production-ready AI services, including monitoring, rate limiting, and reliability controls • Participate in solution design and technical decision-making • Continuously evaluate and experiment with new LLM models and features as they become available • Implement AI safety, security, and compliance controls across the AI lifecycle • Collaborate with cross-functional teams across time zones

• Build multi-step, tool-using agents that plan, retrieve, act, and verify. • Design agent architectures, integrate tools/APIs, and deliver robust execution with safety and observability. • Architect agent loops (planning, memory, retrieval, tool use, self-verification). • Implement tools (functions/APIs/DB queries/files) and MCP-style interfaces. • Combine RAG with agents: chunking, embeddings, retrieval, reranking, grounding. • Add guardrails: execution sandboxes, permissions, rate limits, PII policies. • Build evaluation for agents (task success, autonomy depth, recovery rate). • Optimize for reliability, determinism where needed, and cost.

• Architect and lead the design of scalable data and AI platforms, ensuring performance, reliability, and security across distributed systems. • Develop and deploy agentic AI solutions — autonomous or semi-autonomous systems capable of reasoning, decision-making, and adaptive task execution. • Provide thought leadership in data architecture, analytics, and AI system design, shaping organizational AI strategies. • Collaborate cross-functionally with data scientists, engineers, and product teams to deliver end-to-end intelligent systems. • Evaluate and integrate cutting-edge tools such as Google Cloud Platform (GCP), Vertex AI, or LangChain-based frameworks for advanced reasoning capabilities. • Mentor teams in emerging AI technologies, ensuring best practices in data management, model governance, and ethical AI deployment

• Define and own Sherpany’s AI technical vision and drive strategy across the product • Shape scalable AI platform architecture and ensure robust, secure solutions • Lead design and optimization of on-prem AI systems, maintaining data privacy and compliance • Guide engineering teams with clear technical direction and best practices • Stay ahead of emerging AI technologies and apply them to solve real business problems • Collaborate cross-functionally with product, engineering and go-to-market teams to deliver impactful AI solutions