Founding Customer Success Engineer
Minerva
Founding Customer Success Engineer
Minerva
AI-driven customer behavior modeling platform
Minerva builds AI for marketing leaders. We work together with marketers to automate and accelerate their workflows with AI agents. Our agents augment the end-to-end workflow of the marketer by automating analysis, campaign planning, activation, measurement and reporting.
Customers like the NBA, Ramp, Wander, Hard Rock Stadium Group and Luxury Presence use Minerva to develop a better understanding of their customers and introduce AI specifically built to understand the customer into their commercial organizations. Our campaigns outperform other tools because we built the entire stack: from identity to enrichment to data integration as well as agents to action and report on the analysis.
We've raised $20M from The General Partnership, 8VC, Lingotto, NBA Investments, Topology Ventures, Future Positive, Background Capital and many others. Our team brings together operators and investors from Citadel, Dentsu, Bridgewater, Meta Superintelligence, Growthloop, Amazon and Lazard, alongside engineers and researchers from Berkeley, MIT, Stanford and Cambridge.
Every enterprise account has a team. The account executive owns the deal, and the account manager owns the relationship and the renewal after it. A forward deployed marketer owns the pilot's outcome. A solutions engineer runs the technical evaluation and gets standard accounts live on our product. A forward deployed engineer builds what our product can't do yet.
Customers also use Minerva directly, in the platform and through our API. Those customers, and every question that repeats across accounts, belong to customer success.
Today, when a customer gets stuck, the answer comes from whoever built the feature or whoever is on the account. It's good help, but it's one at a time, it isn't written down, and the same question comes back next week.
You're Minerva's first customer success engineer. Your job is to make sure every customer can get value out of Minerva without waiting on a person, and that no question gets answered twice. You run the support queue, diagnose what comes in, and turn every answer worth keeping into something customers can find on their own. Then you take the patterns to product, so the friction gets fixed at the source.
It's a founding seat. Nobody reports to you on day one, and there's no playbook yet. You'll work most closely with our product and engineering team.
Run the support queue. You own Pylon and our shared customer channels: triage, response times and the first read on everything that comes in.
Diagnose, don't forward. Reproduce the issue, read the data, and either solve it or hand engineering a real diagnosis with a reproduction attached.
Build the knowledge base from zero. Every repeat question becomes an article, a how-to or a short video: how the features and limits work, how to use the API, how to build an audience or write a campaign brief. You keep it accurate as the platform changes.
Make self-serve work. Own the path a new customer takes from first login to first result, and keep shortening it.
Turn friction into product signal. Bring product the questions customers keep asking, ranked by how often they come up, so the fix lands in the platform and not just the docs.
Write the playbook. Escalation paths, response standards and self-serve onboarding checklists: the function a future team will run.
3+ years in customer success engineering, technical support, solutions or a technical account role, ideally at a data, martech, adtech or developer-tools company.
SQL, and comfort with APIs. You can read a schema and work out why a result came back wrong. This is the floor.
You diagnose instead of escalating. You have a real story about a hard problem you chased down yourself.
You write clearly. You've built documentation or a knowledge base that people actually used.
You'd rather fix something once for every customer than a hundred times for one.
You're in New York City or willing to relocate.
Technical documentation you wrote that's publicly live. Link it.
You've run support on Pylon, Intercom, Zendesk or something like them.
Identity resolution, CDPs, match rates or marketing data.
You've made short product explainer videos.
Account management. Our account managers own named accounts, renewals and expansion. You make sure they rarely have to answer a how-to question.
Implementation. Our solutions engineers and forward deployed engineers build customer pipelines, and you know when to hand a problem to them.
Marketing. Our marketing team writes for people deciding whether to buy. You write for the customers who already did.
First 90 days: Pylon is a real queue with response-time standards, the knowledge base covers the questions that come up most, and engineering gets diagnoses from you, not forwards.
First 6 months: repeat questions are falling, more issues get solved without engineering, and new self-serve customers reach a first result faster. A few roadmap items exist because you brought product a pattern with numbers attached.
The numbers you own: the share of questions resolved without engineering, the repeat-question rate, and time to first result for self-serve customers.
$149,000–$189,000 base salary, depending on experience. Meaningful equity. Medical, dental and vision.
Skip the cover letter. Tell us about a customer problem you diagnosed where the obvious answer was wrong: the symptom, what you checked, what it actually was, and what you wrote down afterward so it wouldn't happen again. A few paragraphs. If you've published documentation, link it.
We work in person from our office at 300 Kent Avenue in Williamsburg, Brooklyn.
Minerva uses AI to model consumer behavior and deliver predictive insights for go-to-market teams. It blends a company’s existing customer data with Minerva’s high-fidelity consumer data in a privacy-conscious way, and builds custom predictive models with clients for different personas and products that run in real time through APIs to CRMs, marketing tools, and data warehouses. The platform stands out by involving clients in model development, providing hyper-granular customer context, and offering seamless data integrations. Its goal is to make consumer behavior observable, predictable, and actionable to help organizations improve segmentation, targeting, and personalization.
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