AI Ops Lead - Forward Deploy
Application analysis
AI Ops Lead - Forward Deploy at Mercury is a forward deployed enterprise software role for engineers who want customer-facing technical work with real deployment ownership.
Reading this role
This Technical Leadership role centers on team leadership, customer program ownership, and scaling delivery playbooks. Key signals from the listing: Senior scope.
About Mercury
Enterprise software forward deployed engineers drive adoption, integration, and measurable customer outcomes. The role is anchored in San Francisco, or Remote within Canada or United States, so expect on-site customer work in that region.
Signals in the listing
Stand out for AI Ops Lead - Forward Deploy
- Lead your application with one paragraph tying AI Ops Lead - Forward Deploy to a specific customer or deployment you owned — Mercury hires for shipped outcomes, not tool lists.
- Quantify team and program scale: people managed, number of concurrent customer deployments, and revenue or mission outcomes influenced.
- Explain how you built repeatable playbooks so delivery quality did not depend on one hero engineer.
- This role is tied to San Francisco, or Remote within Canada or United States — mention willingness to work on-site with customers and any existing ties to that market (clients, partners, or domain knowledge).
Stand out at Mercury
- Demonstrate stakeholder management with a concrete example — Mercury will probe for specifics, not buzzwords.
- Demonstrate integration skill with a concrete example — Mercury will probe for specifics, not buzzwords.
- Prepare stories that move from discovery → pilot → production with named outcomes.
- Read recent engineering blog posts, product launches, and customer stories on mercury.com — reference one explicitly in your outreach to show genuine interest.
Tailored from this listing’s title, company, and description. Always verify requirements on the company careers page before applying.
Role description
Mercury is building the financial stack for startups. We're working to make complex financial workflows feel simple, thoughtful, and perhaps even a little magical. You can see some of this in action in our demo dashboard. Most AI initiatives don't stall because the models aren't capable or the tools don't exist. They stall at the last mile: a promising solution gets built, but the way a team works never really changes. AI Operations exists to close that gap. We're looking for a forward-deployed lead who can embed deeply with teams across Mercury, understand how their work actually happens, and turn AI's potential into measurable improvements. You'll spend a few months at a time partnering closely with a particular function. You'll learn the team's work well enough to identify the true constraint—not simply the most tedious task. Then you'll build against it using the tools and infrastructure created by Mercury's AI Engineering team, iterating until the outcome moves and the new way of working sticks. Once it does, you'll make sure the team can carry it forward. You'll leave behind well-built tools, clear documentation, and confident owners before moving on to the next high-leverage problem. You'll be the first person to bring it to teams across the rest of Mercury, beginning most likely with Compliance. That means you won't just run the playbook—you'll help write it. You'll determine what makes an embed successful, how long it should last, what a durable handoff requires, and how AI Operations should decide where to focus next. This role sits somewhere between builder, operator, and change agent. You'll be responsible for helping teams adopt new workflows through thoughtful implementation, training, documentation, and plenty of iteration.