MLSolutionsArchitect

## Description As an ML Solutions Architect, you'll be the technical bridge between clients and delivery teams. You'll lead pre-sales technical discussions, design ML architectures that solve business problems, and ensure solutions are feasible, scalable, and aligned with client needs. This is a highly client-facing role requiring both deep technical expertise and strong communication skills. In the era of Generative AI and autonomous systems, you'll also be responsible for architecting agentic solutions that leverage LLMs, tool ecosystems, and AI-assisted workflows to deliver transformative value to clients. ## Core Responsibilities Pre-Sales and Solution Design (45%) Lead technical discovery sessions with prospective clients; Understand client business problems and translate them into ML solutions; Design end-to-end ML architectures and technical proposals; Create compelling technical presentations and demonstrations; Estimate project scope, timelines, cost, and resource requirements; Support General Managers in winning new business. Client-Facing Technical Leadership (25%) Serve as the primary technical point of contact for clients; Manage technical stakeholder expectations; Present technical solutions to both technical and non-technical audiences; Navigate complex organizational dynamics and conflicting priorities; Ensure client satisfaction throughout the project lifecycle; Build long-term trusted advisor relationships. Agentic Solutions Architecture (15%) Architect agentic AI solutions that leverage autonomous decision-making and tool orchestration; Design MCP (Model Context Protocol) integration strategies for client environments; Evaluate and recommend appropriate agent frameworks (LangGraph, Claude Agent SDK, etc.) for client use cases; Create POC demonstrations showcasing agentic capabilities using AI-assisted development tools Advise clients on build vs. buy decisions for agentic components; Develop reference architectures for common agentic patterns (RAG