- Location
- US
- Type
- Full-time
- Visa
- Not sponsored
- Clearance
- Required
- Source
- ApplicantPro
Description
About the Role
Knexus is a leader in delivering cutting-edge AI solutions to the U.S. Government. By leveraging
Google's Gemini models and our proprietary frameworks, we provide federal agencies with the tools
they need to solve complex data challenges and accelerate mission-critical operations.
We are seeking a high-energy, execution-oriented AI Adoption Specialist to serve as the critical
bridge between our software development team and government end-users. In this role, you will be the
primary "translator" who converts agency pain points into actionable AI use cases, builds and delivers
hands-on training programs, and drives day-to-day user engagement across our deployed Google
Cloud Platform (GCP) solutions.
We operate with a startup pulse. We need a resourceful practitioner who takes extreme ownership,
thrives in client-facing environments, and is eager to get their hands dirty empowering frontline
personnel with AI tools.
Key Responsibilities
• The Technical & User Translator: Act as the direct conduit between non-technical government
end-users and Knexus GCP software developers. Translate messy agency workflows into structured
user stories and technical requirements for engineers; conversely, translate new model capabilities
and technical updates into plain-English capabilities for clients.
• Client Training & Capability Building: Design and lead interactive training bootcamps,
prompt-engineering workshops, and office hours. Build user confidence and competence across all
proficiency levels, moving agencies from initial curiosity to daily operational rely-on.
• Use Case Discovery & Mission Mapping: Work side-by-side with agency stakeholders to map
specific operational bottlenecks to concrete AI features (e.g., Retrieval-Augmented Generation
(RAG), document intelligence, custom prompts).
• User Feedback Loop Management: Collect on-the-ground feedback, user friction points, and
feature requests during client interactions. Synthesize these insights into actionable feedback for our
product and engineering teams to directly influence the development roadmap.
• Collateral & Content Creation: Rapidly produce bite-sized, practical enablement
resources-including "How-To" quick guides, video walk-throughs, cheat sheets, and
agency-specific prompt libraries-that deliver immediate user value.
• Adoption Tracking & User Success: Monitor daily usage metrics, identify "super-users" within
client agencies, and implement targeted engagement interventions where adoption lags.
Qualifications
• Experience: 3–5+ years in technical consulting, software customer success, or technical program
management, with explicit preference for experience supporting U.S. Government clients. The
successful candidate will be comfortable briefing and interfacing with clients directly, both virtually
and in person, and will have experience driving user adoption and tying software tools to U.S.
federal missions.
• Technical Literacy: Working understanding of the cloud, machine learning concepts, and
Generative AI workflows. Google Cloud Platform (GCP)-specific training will be provided.
• Facilitation & Communication Skills: Exceptional live-presentation, workshop facilitation, and
written communication skills. Ability to break down complex technical topics into intuitive,
value-driven concepts. The successful candidate will display clear critical thinking skills.
• Startup DNA: A proactive self-starter who thrives in fast-paced, ambiguous environments,
demonstrates relentless resourcefulness, and takes extreme ownership over customer outcomes.
• Security Clearance: Must be a U.S. Citizen. Ability to obtain or maintain a U.S. Government
Security Clearance (Secret minimum).
Preferred Qualifications
• Experience using or implementing Google Cloud Platform (GCP) AI tools.
• Familiarity with human-centered design (HCD) or organizational change management frameworks
(e.g., ADKAR).
• Active U.S. Government Security Clearance (Top Secret or higher preferred).