What you will be doing:
Embed with GTM and G&A teams (Sales, Marketing, Finance, HR, Legal, Procurement, Customer Success) to identify, scope, and prioritize the highest-impact AI opportunities within each function, and act as both product manager and engineer for these initiatives.
Own the full lifecycle of each solution, from requirements gathering through deployment to adoption measurement and iteration, with a focus on business outcomes.
Serve as the primary technical partner and AI advisor for business function leaders, translating their needs into engineering plans and helping them develop their own AI fluency.
Develop and deliver hands-on AI enablement and training for non-R&D teams, building their ability to use AI tools independently and effectively.
Collaborate with the team to leverage shared infrastructure (MCP servers, RAG systems, evaluation frameworks, guardrails) while feeding back requirements from the field.
Measure and report on AI adoption impact – unlocking new opportunities, process improvements, and capability gains – to build the case for continued investment and to guide prioritization.
Who are you?
7+ years of software engineering experience, with a strong track record of shipping production systems.
Demonstrated experience working directly with non-technical teams to deliver technology-driven transformation.
Exceptional communication skills: you can run a discovery session with a VP of Sales, write a clear project brief, present results to an executive audience, and pair with a junior analyst on prompt engineering, all in the same week.
Strong product instincts and critical thinking. You naturally think in terms of user problems, adoption, and measurable outcomes rather than technical elegance for its own sake.
Comfortable with ambiguity and self-direction. You won't have a detailed backlog handed to you; you'll build it by understanding the business.
Passionate about LLMs, prompt engineering, and AI application patterns (agentic and autonomous workflows, RAG, agents, tool use).
Solid understanding of GenAI, LLMs and foundation models.
Solid familiarity with AI coding tools like Claude Code, Github Copilot, Cursor, or similar.
Hands-on experience building internal/external AI-driven workflows, agentic frameworks, evals, RAGs, MCPs, skills, etc.
Fluent in written and spoken English.
