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We are looking for a Senior Software Engineer to join the AI Engineering team in a role focused on embedding directly with business teams to drive AI transformation. This role is outward-facing: you will sit alongside GTM and G&A functions - Sales, Marketing, Finance, HR, Legal, Customer Success - and fundamentally alter how these teams operate with AI.
Departments outside of R&D are still early in their AI journeys, and they need technically strong partners who can understand their workflows, identify the highest-leverage opportunities, and build the solutions that actually change how work gets done. If you see the value in sitting with a business leader, understanding a painful manual process, and shipping something in a week that saves hundreds of hours, then this role is for you.
Why should you join us?
This is a unique opportunity to own the end-to-end AI transformation of entire functions, with executive sponsorship and real mandate. Youll be working as part of an incredibly strong team of senior engineers at the forefront of AI. The work revolves around learning the latest tech in AI, and leveraging it to change how hundreds of people across the organization work every day.
You'll operate with unusual autonomy: scoping problems directly with function leaders, deciding what to build, shipping it, measuring impact, and iterating. You'll work closely with senior leadership to ensure your work aligns with company strategy, giving you company-wide business impact and visibility.
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 - quantifying time saved, process improvements, and capability gains - to build the case for continued investment and to guide prioritization.