AI Solutions Architect

Role Summary

The AI Solution Architect takes a qualified opportunity and translates it into a practical, deliverable solution. The ideal candidate will have hands-on experience designing and implementing enterprise AI solutions and developing solution architectures, proposals, estimates, implementation plans, and delivery-ready designs.

Key requirements include:

• Strong AI Solution Architecture experience across GenAI, Agentic AI, RAG, Knowledge Graphs, AI Agents, LLM applications, and enterprise AI platforms.
• Experience designing and delivering production AI solutions using platforms such as Azure AI, OpenAI, AWS AI, Google Vertex AI, Anthropic, or Mistral.

Significant presales experience including:

• RFP/RFI responses
• Proposal development
• Solution architecture creation
• Effort estimation and sizing
• SOW development
• Commercial input and pricing support
• Client workshops and technical sales support

The Solution Architect helps answer the question: "How will we build it, what will it cost, and what will it take to implement?"

Important Distinction

AI Solution Architect = Designs, sizes, and sells the AI solution

• When screening candidates, strong AI Solution Architects should be able to clearly articulate enterprise AI solutions they have personally architected end-to-end, including technology selection, proposal development, effort estimation, implementation planning, and delivery handoff.