Lead technical discovery sessions with prospective clients to understand business problems and translate them into feasible ML solutions Design end-to-end ML architectures and author technical proposals, including scope, timeline, cost, and resource estimates Create and deliver compelling technical presentations and demonstrations to both technical and non-technical audiences Support General Managers in winning new business through technical leadership Architect agentic AI solutions leveraging autonomous decision‑making, tool orchestration, and LLM‑based workflows Design MCP (Model Context Protocol) integration strategies for client environments Evaluate and recommend appropriate agent frameworks (LangGraph, Claude Agent SDK, and others) based on client use cases Develop reference architectures for common agentic patterns including RAG agents, multi‑agent systems, and tool‑using agents Build POC demonstrations showcasing agentic capabilities using AI‑assisted development tools Advise clients on build‑vs‑buy decisions for agentic components and assess AgentOps requirements including monitoring, evaluation, and cost optimization Serve as the primary technical point of contact throughout the project lifecycle Manage technical stakeholder expectations and navigate complex organizational dynamics Build long‑term trusted advisor relationships with clients Collaborate with delivery teams to ensure smooth project handoffs Provide technical guidance during project execution Contribute
