Description review

Director of Sales

Director of Sales · Remote · back to the listing

HR standards

45/100

poor

Title ↔ description

84/100

solid

Reads as

Sales Representative

96% confident

What this role officially is

commercial sales representative — ESCO, the EU occupation classification

Commercial sales representatives represent a company in selling and providing information on goods and services to businesses and organisations.

Also known as: field sales representative, technical and commercial sales executive, field sales executive, sales and marketing consultant, business development representative, technical and commercial sales representative

How others title the same work

Large employers

  • EHR Principal Sales Executive, HCLS US Providers Amazon.com
  • Channel Partner Sales Executive Canonical
  • Embedded Devices Software Solution Sales Account Manager Canonical
  • Embedded Devices Software Solution Sales Manager (APAC) Canonical
  • Embedded Devices Software Solution Sales Manager (Americas) Canonical

Startups

  • Account Executive (Full Cycle) AviaryAI
  • Founding GTM / AEs Balance
  • Business Development / Sales Intern Blaze
  • Sales Intern Blaze
  • Account Executive Blee

What the listing never says

  • No section describes what the person would actually do. Scope clarity
  • No pay range published. Candidates cannot tell whether applying is worth their time. Pay transparency

The listing, marked up

Legal Ark AI · First Sales Leader · Job Description · REMOTE (US)
https://legalark.ai and [email protected]
About:
Legal Ark AI serves as the workflow intelligence engine for estate planning practices. Our platform converts unstructured client data into high-confidence, verified facts prior to document generation, empowering legal teams to accelerate throughput, mitigate risk, and scale efficiently without a linear increase in headcount.
The Role:
As our first Director of Sales, you will own new business revenue end to end and build the sales engine from the ground up. You will personally close early deals, figure out the repeatable playbook, and then hire and lead the team that scales it.
What You’ll Own:
- New business ACV: land our core market, estate planning firms with 1 to 25 attorneys, and structure larger deals where they make sense. Large litigation firms are not our market.
- The playbook: build outreach, qualification, demo, and close motions from scratch; find the repeatable recipe, then document and scale it.
- The team: hire and lead SDRs and inside reps as revenue supports, so you move from doing everything to leading a team that does.
- The stack: own the sales tooling (prospecting, CRM, sequencing, automation) and choose what makes the team most efficient.
- Pricing and packaging: partner with the founders on pricing, tiers, security and white glove options, and value gating; be the eyes and ears on what customers will pay for.
- Market signal: feed product and customer success with what you hear in the field, and represent Legal Ark AI at industry events.
What Success Looks Like:
You ramp quickly to a new business quota (target Year 1 new ACV of approximately $3,000,000, roughly 250 seats at current pricing), establish a repeatable motion, and lay the foundation for a team that carries the company toward its growth and exit goals.
Who You Are:
- A proven B2B SaaS closer who has built processes, not just worked someone else’s.
- Experienced selling to SMB and moving deals upmarket; comfortable running the full cycle, from first touch to signature.
- Energized by an early stage, commission only1 structure where your earnings track directly to the revenue you bring in.
- A builder and leader who can hire, coach, and scale a small team.
Someone who can sell a product that augments attorneys and their staff rather than replacing them, and who is comfortable leading with verification and confidence in the data rather than speed alone.
- Legal tech, AI, professional services, or legal sales experience is a plus, not required.
Compensation:
Uncapped commission

How this was produced

Highlights are found by rule, not by a model: each one is a phrase matched at a known position, and every note is a template we wrote. The two scores come from a typed-decision model (Jev) that reads the listing against the official role definition and real listings for the same role, and returns probabilities rather than prose — it never writes any of the words on this page, and never chooses what to highlight.

Deterministic penalty applied to the HR score: 20 points (from 65 before penalties). Reviewed 21 Sep 2026.