This role is in-person in the San Francisco Bay Area. We are looking for A-players who want to work on groundbreaking technology, love to collaborate in person, and we’re willing to pay for it. This person should expect to spend most days in our office close to Embarcadero station.
Overview
Primer sits on top of one of the most underpriced assets in the AI era: real, messy, high-signal go-to-market data.
We’ve spent years building infrastructure that connects companies, people, intent, and outcomes across ad platforms, CRMs, and websites.
Now the question isn’t “can we collect the data?”
It’s “how do we turn this into durable inference, leverage, and products that compound?”
We 4Xed last year. We expect to 10X this year.
We’re looking for a senior technical leader to help define how Primer reasons about data: how we model entities, compute confidence, resolve ambiguity, and serve insights fast enough to feel real-time.
Our stack includes React/Node, Python, Prefect, Iceberg, ClickHouse, and dbt. We process terabytes daily, aim for sub-second query experiences, and make “batch” behave like “real-time” where it counts.
This is a small team. (~20 people)
You won’t have a separate team for “that one thing.”
You’ll sometimes prototype, sometimes refactor, sometimes talk to customers, and sometimes decide not to build at all.
Your Mission
Own Primer’s inference layer end-to-end—from ingestion to serving—so we can turn noisy first and third-party data into trusted, low-latency answers the product can build on.
That means:
- Building a platform that’s reliable (yes: pipelines, SLAs, quality)
- But also defining how we infer truth from imperfect inputs (identity, matching, canonicalization, confidence, and feedback loops)
- And making those inferences available as primitives across the product (features, audiences, insights, recommendations)
You’ll turn diverse APIs and heterogeneous sources into a coherent, queryable system—where “what we know” is explainable, measurable, and fast.
You do not need prior adtech or marketing experience.
If you’ve built or led data platforms in another domain—infra, fintech, devtools, marketplaces, enterprise SaaS—that’s a plus. We care that you’ve built systems that make messy data useful.
What you’ll do
- Be a force multiplier: design and ship scalable batch + streaming pipelines; prototype, profile, and harden critical paths. Code review, mentor, and raise the overall bar.
- Own reliability, cost, and SLOs: instrument observability and capacity; drive ≥99.9% uptime, minutes-level latency, and cost/TB efficiency; lead RCAs and land durable fixes.
- Operate pragmatic inference pipelines that augment data flows (enrichment, scoring, QA with LLMs/RAG); manage versioning, canarying, caching, and evaluation loops.
- Partner cross-functionally to build “data as a product” a la Netflix: define audience and contracts, ensure reliability and ownership, manage lifecycle (versioning→sunsetting), and validate impact through usage.
- Drive pipeline and data lake architecture: run design reviews, document trade-offs/lineage/reversibility, and make clear build-vs-buy calls others can safely build on.
- Scale integrations with third-party APIs and internal services; resolve data conflicts, ensure quality, and support both sub-second query paths and large batch workflows.
What you’ll need
- 6+ years building and scaling production-grade data systems, with a track record in data architecture, modeling, and pipeline design. Leadership experience on data engineering/platform teams.
- Expert SQL (query optimization on large datasets) and strong Python; hands-on with distributed data tech (e.g., Spark/Flink/Kafka) and modern orchestration (Airflow/Dagster/Prefect).
- Experience building and maintaining integrations and data services; solid understanding of concurrency/parallelization and classical processing patterns.
- Familiarity with dbt, columnar databases (DuckDB, Clickhouse), and the modern data stack; IaC, CI/CD, and observability fundamentals. (Kubernetes exposure is a plus.)
- BS/MS in CS/CE/EE (or similar) with strong fundamentals; excellent async communication in distributed teams.
- Bonus: Very good Node.js skills, which will help you onboard quickly.
You’ll succeed by having
- A founder-level bias for action: turn bottlenecks into automated workflows; ship fast, iterate, and measure outcomes.
- Deep empathy for data consumers (analysts, product, business stakeholders) and a pragmatic approach that balances speed, cost, and accuracy for business impact.
- Proactive, honest communication; comfort working hybrid in-person and with a distributed team; ability to set high standards and operate beyond your comfort zone.
- A default-to-teach ethos—mentoring others, documenting schemas/lineage/trade-offs—and the judgment to choose build vs. buy wisely; acts as a clear, calm proxy for data/infra decisions.
What’s in it for you?
- Be part of a different sort of unicorn: an early stage startup focused on profitability with demonstrated, consistent revenue growth (15-20% MoM growth).
- Stand out from the pack. Primer’s engineering team is world class and our patent-pending technology sets it apart from the rest of the GTM space, including areas like real-time data, graphics, inference, and AI recommendations. Real innovation happens here.
- Feel trusted. Our engineers choose how they manage their time and spend >90% of it outside of meetings. We value outcomes above all else.
- Get founder experience without having to write investor pitches. Keith (CEO) and Juan (CTO) have a proven track record inside of startups (Y-Combinator, Wheelhouse, Modsy, Eden) as well as combined decades of industry experience from places like BlackRock and Dropbox. This role will partner closely with founders and let you see how the sausage is made.
- Our culture is high-achieving, genuinely kind, and collaborative.
BENEFITS
- AI subscriptions (Cursor, Claude Code, and monthly subscription to frontier model)
- Unlimited vacation: required 5 weeks paid time off.
- Retirement planning (401k)
- Generous parental and family leave.
- Comprehensive health plans.
- New equipment and office stipend of $1,500.
- Support for personal and professional development outside of work.
- Annual team offsite.
- Diverse and fun team.
What is the interview process like?
We pride ourselves on being respectful of your time. Our interview process starts with an introductory call with one of our founders, followed by a take home exercise, then a half-day session to meet our team. We typically provide a decision within 24-48 hours from the last meeting and aim to conclude the whole process within a week, provided that it works with your schedule.
What do I do now?
If this sounds like an interesting opportunity, please apply by email at careers@sayprimer.com, and include your LinkedIn profile, CV, Github repos, or anything else that you think might give us a good sense of who you are.