AI Operations Lead

Arcadia is the AI-powered energy intelligence platform for businesses. We replace fragmented tools and manual workflows with one platform to pay utility bills, buy energy, and advance sustainability — across every location, at enterprise scale. Trusted by Fortune 2000 companies, Arcadia combines unified data, AI-powered analytics, and expert advisory to help enterprise teams save money, mitigate risk, and cut carbon.

About the role

The AI Operations Lead is the product owner of Arcadia's AI transformation. You will work directly with teams across the company, in product, engineering, go-to-market, finance, and operations, to learn how the work actually happens, define the highest-leverage AI opportunities, and drive them from idea to adopted workflow. In practice that means owning the roadmap and requirements for the Claude skills, agents, and workflows teams adopt, partnering with engineering to build them, and establishing the patterns, standards, and champion network that let those wins compound long after you have moved to the next team. The role reports into R&D Operations and carries a mandate that spans all teams. Outcomes are the bar: an AI workflow earns its place by what it changes for the team, not by how novel it is, and that standard decides what scales and what gets retired.

Responsibilities

• Embed team to team. Rotate through teams across the company to map current-state workflows end to end: where time goes, where decisions stall, where handoffs between teams and functions compress or disappear. Translate that into a prioritized set of high-leverage AI opportunities for each team, backed by a clear point of view on sequencing and expected impact.
• Own the product definition for Claude skills and workflows. Write the requirements, define the success criteria, and set priority for the reusable Claude skills, agents, and automations teams adopt, then partner closely with engineering to ship them. Redesign the workflow around the capability and outcome rather than bolting AI onto an unchanged process.
• Engage and grow the champion network. Every team is expected to have an AI champion. In many cases you'll help identify who that should be, then enable them to extend, maintain, and evangelize workflows after you've moved on, so capability compounds instead of depending on you.
• Codify what works. Turn every win into a reusable pattern (a shared library of skills, templates, and playbooks) so a solution built for one team becomes a starting point for the next.
• Keep builds safe and compliant. Partner with the governance lanes (Security & Compliance; AI Technical Approach) so every workflow meets Arcadia's data-handling, classification, and human-in-the-loop standards by design.
• Measure and report impact. Track adoption, time saved, and workflow outcomes. Make the case for scaling what works and retiring what doesn't, and feed signal back to leadership.

What success looks like (first two quarters)

• A repeatable engagement model for embedding with a team, mapping its workflow, and defining and shipping its first production AI workflow in partnership with engineering.
• A growing, self-sustaining champion network across the company, with champions independently maintaining and extending what's been built.
• A shared skill-and-workflow library that measurably shortens the time to stand up the next team.
• Documented adoption and time-saved outcomes that move teams out of the pilot loop and into scaled use.

Requirements

• 5–8 years of product management, workflow, or process-design experience, spotting where work breaks down across departments and turning that into prioritized, well-scoped initiatives that teams actually adopted, not just launched. Extra credit if you've shipped AI-enabled workflows or automations directly.
• Strong workflow- and process-design instincts. You can sit with a team in any function, see the real operating model underneath the org chart, and define what needs to change.
• Fluency in translating a business problem into clear requirements and success criteria that engineering can build against, and in evaluating tradeoffs in a build even if you are not the one writing the code.
• The interpersonal range to win trust across very different teams and cultures, and to bring a skeptic along.
• A bias for reusable systems over heroics. You'd rather define the pattern once than solve the same problem ten times.
• Comfort operating in ambiguity inside a fast-moving, post-acquisition organization.

Nice-to-haves

• Experience standing up enablement, center-of-excellence, or champion-network models.
• Familiarity with AI governance concepts (data classification, human-in-the-loop, security review).
• Exposure to AI-native operating models at high-performing software organizations.
• Background in R&D, product, or engineering operations.
• Hands-on experience building Claude skills, agents, or similar automations, though this is not required.

Benefits

• "Remote first" culture - work anywhere in the US as long as you have a reliable internet connection
• Flexible PTO - no accrued hours and no limit on the number of vacation days exempt employees can take each year
• 11 annual holidays
• 10 days sick leave
• Up to 3 weeks bereavement leave
• Up to 4 weeks of caregiver leave
• Military leave for eligible services or events
• 2 volunteer days off
• 2 professional development days off
• 10 weeks paid parental bonding leave for all parents and additional medical recovery time for eligible employees
• 75-95% employer cost coverage for medical, dental, and vision benefits for employees and dependents

Pay

Target annual compensation range for this role will be $127,500 - $228,400. There will also be a competitive benefits and equity (bonus if applicable) component to the package. The exact compensation at which this job is filled will be determined by the skills, experience, and location of the qualified candidate.

Arcadia is unable to offer visa sponsorship for this position at this time.