About Coval
Coval is the evaluation platform for enterprise voice AI, built by former Waymo engineers applying autonomous vehicle testing standards to help companies deploy and scale conversational agents to 10s of millions of calls a month. The platform gives engineering, product, QA, and operations teams the infrastructure to stress-test agents across millions of realistic scenarios before launch, monitor every live conversation in production, and continuously sharpen performance through human-in-the-loop review. Trusted by more than 60 customers like Chime and Zoom, Coval is the operations layer for voice interfaces, the next platform after mobile and web.
The role
We're looking for a Deployment Strategist who owns the full lifecycle of an account after signature, driving adoption and expansion into new use cases and teams. You do that by being technical enough to catch what's happening (and not happening) in the deployment, and commercial enough to translate it into the relationship and the ROI behind it. This role rewards people who can sit inside real complexity and still find the two things that actually matter, and who can work cross-functionally with product and engineering to turn what they're seeing into the roadmap.
What you'll do
Own the commercial outcome
Take full ownership of your accounts' adoption and expansion, with compensation directly tied to their growth. Develop account plans, maintain an accurate view of the pipeline, and navigate conversations around scope and pricing. Your goal is to build successful, lasting customer relationships that expand into new use cases and teams.
Manage the relationship strategically
Lead engagements from the beginning. Run kickoffs that align stakeholders across product, engineering, QA, and leadership on the goals of the deployment, how success will be measured, and who owns each part of the work.
Hold the room. Different stakeholders show up with different incentives. Get them aligned.
Go deep enough technically to be credible
Diagnose and prioritize. Connect a customer's business tension to a specific, testable decision. Not every problem is a good first deployment. You'll learn to spot the ones with pressing deadlines, narrow enough scope to isolate what's being tested, and the decision owner who will act on the result.
Get your hands dirty in the platform. Design personas, write test cases, configure metrics, and set up the evaluation framework for the customer's product. Build custom methods when the standard tooling doesn't answer the question the account needs.
Feed the product organization
Build durable knowledge, not one-off saves. Every account teaches you something that applies to the next one. Write it down. Flag the pattern. Build the evidence that steers our product roadmap.
Partner with FDEs and product/eng to close the gaps. When an account needs something the platform doesn't do yet, you're the one who knows whether it's worth building, and you work directly with the team that builds it.
What you'll need
- You've owned commercial outcomes before: adoption, renewal, expansion, or quota in some form, not just delivery.
- Experience in account management, technical account management, or a customer-facing role where the relationship's health was your job.
- You've done deployment, implementation, or technical work where you owned a technical outcome, not just a relationship. Solutions engineering, forward-deployed engineering, technical customer success, or similar.
- You can hold a room of stakeholders with different incentives, a champion, a skeptic, a validator, and get them aligned on what evidence would change their mind.
- You have product instincts: you can tell the difference between a one-off customer ask and a gap worth closing, and you're comfortable making that case to the product team.
- You're honest about tradeoffs out loud, including when you're wrong.
- Comfort with ambiguity at an early-stage company where the role isn't fully defined yet, because part of the job is defining it.
Nice to have
Experience with voice AI, conversational AI, or customer facing AI agents.
A track record of building something repeatable out of what started as a one-off.
Experience working at an early stage startup
Compensation & details
- Salary: $150k - $250k OTE, equity
- Location: San Francisco office, 5 days a week
- Reports to: Alejandra Vergara
- Travel: expect onsite work with customers
Benefits:
- Healthcare, Dental, & Vision coverage
- 401K
- Pet friendly-office
- Free gym membership
- Free lunch and dinner when working in the office
- Unlimited PTO

