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Open nowPosted 15 days agoWe saw it 77 min after it went up

AI Product Lead (Principal Product Manager)

EverQuote15 open roles

Pay
$174,800 – $205,700 a year
Where
Remote
Work mode
Remote
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Your applicationOpen nowAI Product Lead (Principal Product Manager)EverQuote · Remote

  1. YouYes, apply to this one.

  2. CV RocketCV written for this posting.

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The clock on this job

Early applications get read.

13.8% of postings close within 7 days. Measured by our own scanner across the market. EverQuote postings stay open a median of 55 days.

Share of postings closed within
  1. 2.2%1 day
  2. 4.7%3 days
  3. 13.8%7 days
  4. 22.3%14 days
  5. 37.8%30 days
  6. 59.0%60 days
This job: posted 15 days ago

EverQuote median: 55 days open

The posting

Location

Remote

About Us

EverQuote is a leading AI-powered growth solutions partner for regulated property and casualty insurance entities, enabling the largest insurance carriers and thousands of agents to maximize customer acquisition across digital channels. Fueled by our proprietary data assets and our AI traffic engine, EverQuote is transforming the way providers attract and engage consumers to grow market share.

Joining our team puts you at the forefront of this transformation. You will collaborate with a group of builders to solve complex problems and reshape a massive industry. If you want to drive real-world impact and do the best work of your career, you’ve found your home. We move fast, follow the data, and hold ourselves to high standards. If that's how you work too, this is the role for you.

About the Role

As the AI Product Lead you will own a product unlike anything we have built: an insurance marketplace that AI agents use to shop on a person’s behalf. When an AI agent shops for insurance, you will make the AI- insurance shopping experience the one it trusts and can buy through. You will help shape what agentic insurance shopping looks like before the market arrives.

You own the agent-facing product: the data an agent sends and gets back, the recommendation and reasoning we return, the MCP server and skill that let AI platforms connect to us, and the trust signals that make an agent willing to rely on us. You own the roadmap, the testing of how well the agent performs, and the relationships with the AI platforms whose agents call us. Often your customer is another AI agent rather than a person, and the product has to earn that agent’s trust

What You’ll Do

  • Define and own the product roadmap for the marketplace, balancing what agents need, what the architecture allows, and where the business is going.
  • Own testing and quality: build and maintain the eval sets, name the ways the agent can go wrong, and decide what counts as a good agent interaction.
  • Track how the agent is doing: completion, accuracy, speed, and how often a handoff is followed through.
  • Build quick prototypes while the problem is still fuzzy: stand up agent flows and put them in front of real and test agents to learn before engineering commits.
  • Take what we learn about how agents shop and turn it into real changes in the data model, the reasoning we expose, and the architecture.
  • Work with the AI technical lead and engineers on architecture trade-offs, cost, and speed, and keep the shopper’s and the calling agent’s interests in every decision.
  • Build relationships with AI platforms to learn how they find and route to agents, and bring that back into our design.
  • Work in the open. Help publish our mission, experiments, and findings.
  • Give leadership clear, regular visibility into progress, what we are learning, and risks.

What You Bring to the Team (Qualifications)

  • Experience building and shipping real AI products, ideally from an AI lab, an AI-native company, or a team that has put LLM or agent products into production. You have done this, not just studied it.
  • Comfort with testing AI: you can take a fuzzy goal and walk through how you would test it, where it would fail, and when you would roll it back, before reaching for a model.
  • A working understanding of agent systems: LLMs, how agents are put together, retrieval, orchestration, guardrails, and the cost and speed trade-offs that come with them. You do not need to build the models, but you need to talk about them with engineers.
  • Enough technical depth to hold your own in an architecture or code review and ask a sharp question. Comfort with light Python or SQL to look at data and prototype.
  • Strong product instincts and comfort with ambiguity. You can make progress on loosely defined problems.
  • Clear communication with both technical and non-technical people, and the habit of leading with data.
  • A continuous learner, with grit and a bias for action in a space where the standards change month to month.
  • 8+ years in product management, engineering, or closely related work at a technology company, including senior ownership of a product area.
  • A track record of leading large, ambitious projects with a small team and delivering them. We care more about what you have shipped and the judgment you showed than about the size of your org.
  • Proven experience building and shipping AI or agent products to production, ideally from an AI lab or an AI-native team.
  • Detail-oriented, with a history of strong, dependable delivery in a fast-moving, entrepreneurial environment.
  • Fluency in SQL for your own data analysis, and comfort reading or writing light Python to prototype.
  • Strong strategic thinking paired with methodical execution. You can set the direction and then deliver it.
  • Excellent communication across all levels of an organization, technical and non-technical.
  • Experience defining requirements for complex technical systems or platforms.
  • A history of teamwork and a bias for action.

Nice to Have (But Not Required)

  • Insurance or fintech experience.
  • Familiarity with MCP, A2A, agent registries, or the emerging agentic-commerce standards.
  • Experience working or publishing in open developer communities.

________________________________________

The base salary offered for this position is determined by several factors, including the applicant’s job-related skills, relevant experience, education or training, and work location. The base salary for this full time remote role is $174,800 - $205,700.

In addition to base salary, our total compensation package may include participation in variable cash bonus programs, equity, and a comprehensive range of health, welfare, and wellbeing benefits based on eligibility which are designated by role.

Your recruiter can provide more details about the specific salary/OTE range for your role during the hiring process.

This role is not eligible for immigration sponsorship, now or in the future. Candidates must have current, unrestricted work authorization in the United States.

EverQuote is an equal opportunity employer and considers all qualified applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, ancestry, age, disability, genetic information, pregnancy or a pregnancy-related condition, veteran or military status, or any other protected characteristic. Reasonable accommodations are available for applicants with disabilities and for sincerely held religious beliefs or practices, upon request.

For more information, visit https://investors.everquote.com and follow on LinkedIn.

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