Account Executive
About Discernis
Discernis builds AI driven document intelligence for high stakes legal work. Because our customers handle privileged and regulated matters that most cloud AI cannot touch, we run on premises and in customer controlled environments as well as in the cloud. That makes security, reliability, and reproducibility core product features, not afterthoughts. We work with AmLaw firms and enterprise legal teams where accuracy, explainability, and data control are non negotiable.
The Role
You will own enterprise deals end to end, selling a technical, high value product into large law firms and corporate legal teams. These are considered, six and seven figure purchases with multiple stakeholders, long cycles, and real security and procurement scrutiny. You will work directly with our founder in a company where closing the right customers is the single most important thing we do. The upside is uncapped, the accounts are marquee, and the people who land them will be rewarded for it. This is a role for someone who wants to sell a product that genuinely matters to its buyers and to own the kind of deals most reps never get to touch.
What You Will Do
Own the full sales cycle for enterprise legal accounts, from qualification through close
Run complex, multi stakeholder deals involving practice group leaders, IT, security, and procurement
Develop and manage a pipeline of AmLaw firms and enterprise legal teams
Lead customer discovery that connects our capabilities to real workflows in litigation, investigations, and legal discovery
Navigate security reviews, on premises deployment questions, and legal and procurement processes alongside our technical team
Partner with sales engineering to run compelling demos and proofs of value
Forecast accurately and keep the pipeline clean in our CRM
Feed what you learn in the field back to product and leadership
What You Bring
A track record of closing complex, high value B2B deals, ideally enterprise SaaS or technical products
Experience with long, multi stakeholder sales cycles and six figure or larger contracts
Ability to sell a technical product credibly to sophisticated, skeptical buyers
Comfort navigating security, procurement, and legal review processes
Strong discovery, qualification, and pipeline management discipline
Excellent written and verbal communication
Bonus: experience selling into law firms, legal, or another regulated enterprise market, or selling eDiscovery, legal tech, or infrastructure and security products
Why This Role
Uncapped earning potential, with a compensation package built to reward the people who land marquee accounts
Meaningful early equity in a company at the ground floor
Direct work with the founder and VP of Sales on the deals that define the company
A product your buyers genuinely need, sold into a market where few competitors can follow us on premises
Location
This role has versatility in location, with a preference for major markets (LA, SF, Chicago, Dallas, Houston, NYC, DC)
Skills Required
- Track record of closing complex, high-value B2B deals, ideally in enterprise SaaS or technical products
- Experience managing long, multi-stakeholder sales cycles and contracts worth six figures or more
- Ability to credibly sell technical products to sophisticated buyers
- Comfort navigating security, procurement, and legal review processes
- Strong discovery, qualification, and pipeline management skills
- Excellent written and verbal communication skills
- Experience selling to law firms, legal organizations, regulated enterprises, eDiscovery, legal technology, infrastructure, or security products
What We Do
Discernis builds AI-native document-intelligence software for legal professionals handling litigation, investigations, and other high-stakes work. Its platform analyzes entire document collections—often millions of files—using cross-document analysis to surface key evidence and inform case strategy. Designed for security-sensitive customers, it can run on premises, in a customer-controlled cloud, or in hybrid environments, keeping inference within the organization rather than using third-party AI APIs.
