Responsibilities
- Drive Adoption Across the Organization
- Coordinate cross-functional AI initiatives
- Assist in identifying high-value AI opportunities across business units, prioritize by feasibility, business impact, and speed to value
- Serve as the internal point of contact for AI tool rollout, feedback, and iteration
- Track whether deployed solutions are actually being used. Measure outcomes and improve what isn't working
- Help organize knowledge-sharing sessions and documentation to promote practical use across the organization.
- Implement & Iterate on AI Solutions
- Work directly with vendors and internal teams to configure, test, and tune AI tools for specific use cases
- Support the development lightweight automations and AI workflows that business teams can operate independently
- Work closely with the Security and Governance team to remove blockers and ensure the safe use of AI tools.
- Stay on the Frontier
- Continuously evaluate new AI tools, models, and platforms — synthesize what's actually relevant for the business
- Maintain fluency in model capabilities and limitations so you can make smart build-vs-configure-vs-buy calls
- Share signal, not noise: translate external AI developments into concrete internal recommendations
Requirements
- At least 1-2 years of experience in Product Management, Project Management, or Software Engineering.
- A track record of operationalizing new technologies within a business and measuring their impact on organizational efficiency.
- Strong business intuition. You can map a messy process, spot the friction, and figure out where AI creates real leverage
- Heavy, habitual AI user. You try every notable tool on release and have a formed opinion on each one. Can write, debug, and iterate on prompts for real-world tasks.
- Hands-on with workflow automation tools (n8n, Make), agentic AI tools (ChatGPT Agent, Claude Cowork, Manus) and coding assistants (Cursor, Claude Code, Antigravity)
Nice to Have
- A background in computer science and/or process improvement.
- Exposure to enterprise AI deployment — API integrations, RAG pipelines, or LLM evaluation approaches.
- Experience building internal productivity tools or leading digital transformation initiatives.
- Familiarity with change management principles.
