AI Deployment Lead

Design and deploy agent and multi-agent workflows on top of GRACE

• Drive adoption through training and hands-on delivery
• Own the feedback loop back to product, engineering, and design
• Measure and report on adoption
• Drive engineering excellence and startup-like execution

• 5+ years of experience in a customer-facing technical role such as product management or product operations, technical account management, solutions engineering–with an instinct for prioritizing feedback and translating it into requirements.
• Background in solutions engineering, technical account management, sales engineering, or forward deployed work.
• Proven experience in high-velocity environments (tech startups and/or large-scale industry roles) where you owned a customer or stakeholder relationship end to end.
• Hands-on experience building with modern LLM tools, including prompt engineering and agent or workflow construction.
• Demonstrated ability to train non-technical audiences on technical tools.
• Excellent active listener with a low ego and collaborative approach, comfortable being the person who listens more than they talk in a room.
• High agency, with the ability to navigate ambiguity and figure out the next right step without a lot of direction.
• Genuinely customer-obsessed, with real curiosity about how people actually work, not just what they say they need.
• Background in product management or product operations, with an instinct for prioritizing feedback and translating it into requirements.
• A track record of driving adoption of a new tool or process across a busy organization.

Preferred Qualifications:

• Experience with agent frameworks or workflow builders (LangChain, CrewAI, low-code tools like Zapier or Make, or similar).
• Experience with or strong familiarity with Model Context Protocol (MCP) or similar protocols.

Education: Bachelor’s degree or equivalent practical experience.

Location: Remote Clearance: Ability to obtain HHS Public Trust.

This role is ideal for someone who has worked directly with customers or internal teams in high-velocity environments (startups and/or big tech), listens more than they talk, and wants to apply practical AI across an enterprise. You’ll do this while helping teams understand GRACE’s capabilities and limits within the constraints of our mission and the broader federal environment (privacy, security, safety, and responsible use by default).