AI Enablement Engineer

Impact the Moment

We're looking for an AI Enablement Engineer to join our AI Enablement team; someone who embeds directly with business teams to understand how they work today, and helps them reimagine those workflows using AI. This is fundamentally an engineering role, but the job isn't to build a custom solution for every workflow you touch. It is to turn what you learn into repeatable patterns, reusable proof of concepts, and skills that let teams keep moving on their own.

In the near term, you'll help support the rollout of our enterprise AI tools across the organization, working through the technical details of onboarding and adoption. But the real mandate is longer term and bigger: helping the company become genuinely AI native by continuously finding where AI tools, existing ones and new ones as they arrive, can meaningfully change how business teams get work done, and then building the patterns that make those changes scale.

This role sits between engineering and the business. You need enough technical depth to build real prototypes and understand how these tools work under the hood, and enough business fluency to sit with a team, understand their workflow, and help them see a genuinely different way of working. We're also looking for someone who is an expert-level practitioner of our enterprise AI tools, especially M365 Copilot and Claude, not just someone who knows about them.

You should be able to get more out of these tools than most people at the company, and use that depth to show others what's actually possible.

This is a remote position open to applicants authorized to work for any employer within the United States.

• Support the technical rollout of our enterprise AI tools: onboarding, integrations, access issues, and the practical problems that come up as teams start using it.
• Build early proof of concepts with pilot teams that show what the tool can do for their specific workflows.
• Partner with other functions like cybersecurity, legal, data ethics and training on the rollout so the technical details don't become adoption blockers.

• Embed with business teams to understand their workflows in depth, and identify where AI can change how the work gets done, not just speed up one step in an old process.
• Design and build proof of concepts that show a team a genuinely new way of working, then help them carry it into everyday use.
• Identify and enable foundational capabilities like connectors and any other integrations.
• Turn what works into repeatable patterns: reusable prompt libraries, skills, plugins, workflow templates, integration recipes, and reference builds that other teams can pick up without needing a dedicated engineer.
• Feed what you learn from the field back into company-wide best practices, training, and governance, in partnership with the rest of the AI Enablement team.
• Teach and transfer knowledge, not just solutions: help teams build enough AI fluency to extend and adapt what you've built themselves.
• Scout new AI tools and capabilities as they become available within the company, and form a clear point of view on what's worth enabling and where.
• Guide teams toward optimal, cost-efficient use of enterprise AI tools: right-sized models, well-scoped prompts, and workflows that get strong results without wasting spend.

• An expert-level practitioner of enterprise AI tools like M365 Copilot and Claude: you know these tools inside and out, push them well past basic use cases, and can teach others how to do the same.
• A real engineering background: you can prototype, script, and build integrations yourself, not just advise on what's technically possible.
• A product mindset: you default to designing and building for reuse and self-service rather than one-off solutions for a single team.
• Comfortable embedding with a business team long enough to deeply understand their workflow, but disciplined about generalizing what you build so it outlives that one engagement.
• Strong proof-of-concept instincts: you'd rather get something real in front of users quickly than over-engineer before you know it's worth building.
• Curious and fast-moving with new AI tools and capabilities, comfortable evaluating and adopting new ones as the landscape shifts.
• A strong communicator who can sit with a non-technical business team and guide them through rethinking how they work.

• Deep, hands-on…