IT & AI Enablement Engineer

Salary Range: $110,000 – 130,000

About the Role

We’re a software company actively rolling out AI tools across our organization and need someone to help us do it right — not just technically, but in a way that the rest of the business can actually adopt and use. This is a hands-on role with real ownership. You won’t be handed a detailed story and asked to close it. You’ll be handed a problem and expected to think it all the way through — from how it gets built to how it gets deployed, monitored, supported, and used by people who aren’t technical.

You’ll work closely with IT leadership to scope and deliver AI-powered tooling and automations across the business. You’ll also be the person who helps others in the organization understand and use these tools — training them, supporting them, and figuring out how to scale what works for one person into something that works for everyone.

If you’re the kind of engineer who finishes things — not just the code, but everything around it — and who gets energy from seeing the whole business benefit from something you built, this role is for you.

What You’ll Do

Build and own end-to-end

• Take problems — not just requirements — and think through the full solution: build, deployment, security, monitoring, supportability, and ease of use
• Deliver things that are actually done: documented, deployed, observable, maintainable, and usable by non-technical people
• When you solve a problem, ask whether that solution works for one person or for everyone — and build toward the latter. See patterns across business units and bring that thinking proactively to IT leadership

Business engagement

• Sit in on calls with IT leadership and business units to understand problems at their source — not just receive filtered requirements
• Ask the right questions to understand what people actually need, not just what they asked for
• Work alongside non-technical business users collaboratively, not as someone who takes a spec and disappears

Training and enablement

• Train people across the business on AI tools — Claude Code, approved integrations, and whatever comes next
• Build training that scales: guides, walkthroughs, and resources that don’t require you to be in the room
• Be the person who makes tools feel accessible to people who would otherwise be intimidated by them

What We’re Looking For

Experience

• 3–6 years of software development or technical engineering experience — enough to think like a developer, not necessarily to write code all day
• Has worked in environments where they owned problems, not just stories — small teams, startups, or roles where there was no one else to figure it out
• Hands-on experience building and deploying in cloud environments — AWS, GCP, or Azure — including familiarity with how applications get hosted, monitored, and maintained in production
• Hands-on experience with AI coding tools — Claude Code, Cursor, Copilot, or similar — on real work, not just experimentation
• Comfortable with GitHub, scripting, and automation at a working level
• Has built and shipped things that other people use — and has felt the difference between “technically complete” and “actually done”
• Degree in Computer Science, Information Systems, or a related technical field

How you think and work

• You see the whole problem — build, deploy, secure, monitor, support — not just the feature in front of you
• You’re calibrated on new technology: you can evaluate whether something provides real value before committing to it, and you’re not chasing every new tool that comes out
• You communicate clearly with people who aren’t technical — you can explain what something does, why it matters, and how to use it without jargon
• You’re easy to work with across the business — curious, patient, and genuinely interested in understanding what people need
• You bring problems and ideas to leadership early rather than disappearing and surfacing issues late
• You know when something needs a decision from someone else — and you ask rather than assume

What we’re not looking for

• Someone who has only worked in large org environments where work was handed to them in detailed stories
• Someone who will come back and say “done” when the feature works but nothing around it is in place
• Someone who needs to be told every next step after delivering the first one