Job Title: AI Deployment Lead
Overview:
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 our capabilities and limits within the constraints of our mission and the broader federal environment (privacy, security, safety, and responsible use by default).
Key Job Responsibilities:
• Work directly with program teams to identify high-value workflows, and build working prompt structures, agent chains, and templates that solve real problems
• Build a reusable library of prompt patterns, agent templates, and playbooks other teams can pick up directly
Drive adoption through training and hands-on delivery:
• Run onboarding sessions, office hours, and team-specific training tailored to how different groups work
• Grow a network of power users and champions across program teams
Own the feedback loop back to product, engineering, and design:
• Sit in on real workflows, gather what's working and what's broken, and turn it into clear, prioritized input for the team
• Translate ambiguous requests into specific product requirements
Measure and report on adoption:
• Track usage, training completion, and workflow adoption across the agency
• Build a clear view of where adoption is working and where it needs attention, and bring it to leadership regularly
Drive engineering excellence and startup-like execution:
• Establish and improve training materials, playbooks, and best practices as our capabilities evolve
Basic Qualifications:
• Bachelor's degree or equivalent practical experience.
• 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.
• 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.