About Exa
Exa is building a search engine for the AI era. Our Search API currently powers Agents, Fortune 500s and AI labs as we transform an industry that hasn’t been disrupted since the 90s. We're a largely SF-based team of ~100 from Harvard, MIT, Meta, Google Research, ex-founders & dropouts alike.
We recently raised an $85M Series B from Benchmark, and we are rapidly building the most intelligent search engine in history. We’re high agency, low-ego, and united by the feeling that this is one of the last problems worth getting right.
The role
Data Partnerships at Exa is focused on creating the greatest knowledge ecosystem with our world-class partners. Members of the team run end-to-end data licensing deals including portfolio strategy, outbound, negotiation, close, and renewal.
We're hiring a partner who can run deals shoulder-to-shoulder with the existing team so we can move faster and land more. You'll own a portfolio of partners end-to-end, working closely with legal/privacy and engineering to take each one from outbound through to a live, integrated, paying partnership.
This is a builder seat, not an SDR or AE role. Expect to operate with founder-level autonomy on the deals you own.
What you'll do
- Run the new logo cycle for your portfolio: targeting, outbound, discovery, pitch, technical evaluation, commercial structuring, negotiation, signature.
- Exercise taste and prioritization when selecting the data partners being considered for our platform.
- Structure commercial terms: flat fee vs revenue share vs data swap vs hybrid; term, MFN, data rights (training, caching, redistribution, retention).
- Drive contracts to signature alongside legal: MSA, DPA, Order Form, IP, indemnification, termination, audit, privacy/security review.
- Hand off cleanly to the data engineering team for ingestion, schema mapping, QA, and ongoing freshness/quality SLAs.
- Own renewals and expansions for a subset of accounts: QBRs, deal performance, expansion pathways, renegotiation leverage from usage data.
- Bring the voice of the partner back into product: data gaps, query patterns, market shifts they see before we do.
- Collaborate in building out the Data Partnerships team over time.
Who You Are
- You've owned complex commercial deals end-to-end (BD, partnerships, enterprise sales, or data licensing) and have personally closed contracts in the six- to seven-figure range.
- You're comfortable with the substance of data agreements: DPAs, training rights, redistribution, indemnification, MFN clauses. Direct experience with privacy law (GDPR/CCPA) is a strong plus.
- You can pick up technical concepts fast (schema, coverage, freshness, ingestion) and speak to them confidently with engineering counterparts at our partners.
- You're comfortable in a high-velocity startup where the portfolio shifts regularly.
Bonus
- You've worked closely with in-house counsel on data licensing or privacy reviews. Familiarity with the kind of legal work owned in-house at Exa (MSA/DPA negotiation, privacy posture, audit response) means you'll close deals faster.
- You understand how data pipelines actually work: ingestion, schema mapping, monitoring, quality SLAs. You don't need to write the code, but you should be able to scope an integration with an engineer and translate it cleanly to the partner's technical lead.
This is an in-person opportunity in San Francisco. We're happy to sponsor international candidates (e.g., STEM OPT, OPT, H1B, O1, E3). In addition to premium healthcare benefits (medical, dental, vision), we also offer fertility benefits and a monthly wellness stipend to all of our employees.
Skills Required
- 1+ years in a legal role, with a JD
- Experience in contract negotiation, ideally having worked with privacy law
- Ability to understand highly technical concepts and communicate with stakeholders
- Comfort in a fast-moving, high-growth startup environment
What We Do
Exa was built with a simple goal — to organize all knowledge. After several years of heads-down research, we developed novel representation learning techniques and crawling infrastructure so that LLMs can intelligently find relevant information.









