Revenue Operations Leader

**About Us
**At Litify, we're powering a new era for the legal industry. Since its founding in 2016, Litify has helped law firms and corporate legal departments turn operations into impact through its leading AI-native Platform of Action. 

Over 55K legal professionals and 450+ enterprise clients across plaintiff, insurance defense, immigration, and the Fortune 500 trust Litify to combine cloud-based technology, configurable AI-native workflows, agentic AI, and powerful business analytics into one open ecosystem that moves legal teams from systems of record to systems of action.

Backed by Bessemer Venture Partners and recognized as an Inc. 5000 and Deloitte Technology Fast 500 fastest-growing private company, Litify is at the center of legal innovation. Headquartered in New York, we're building the last legal platform our customers will ever need.

**About the Role
**Reporting to the CRO, we’re seeking a director-level Senior Revenue Operations Leader to solve 4 things:

• Define & Deliver a simplified, AI-forward GTM tech stack that maximizes the capture, flow, and utilization of data across the revenue process — reducing administrative burden while improving measurable outcomes.  This includes cultivating and maintaining a clean SFDC instance capable of serving as a foundation for AI initiatives.
• Elevate a business partner who operates cross-functionally: understanding, anticipating, and solving business needs through data-driven modeling and deliverables.  Serves as the trusted advisor to the CRO.
• Create company-wide consistency (when applicable) across the tech stack and reporting.
• Develop RevOps into a GTM partner for the CRO to develop, maintain, & enforce a strong operating cadence that produces definable value up and down the GTM org structure. 

This is not a reporting-and-infrastructure seat. It is a player-coach leadership role: hands-on in the RevOps work itself, while building and leading a team that grows with the company.

Targeted Sample Outcomes:

• A simplified, AI-forward tech stack — CRM architecture and reporting as its foundation, with AI tooling or AI builds that are actually landed and adopted by reps, proven with usage data, not a vendor selection exercise.
• Capacity and Forecast models the business trusts and can defend — bottoms-up, stage-exit criteria, conditional close rates — the data-driven modeling that makes this seat a real business partner, not just a reporting function.
• Diagnosis that turns into field-level intervention: corrective actions that reach reps with a measurable before-and-after.

Role Responsibilities

Revenue Operations & Systems:

• Own CRM architecture, hygiene, and stage-gate discipline across the full sales cycle.
• Build and maintain the bottoms-up capacity model the team's growth targets are set and defended against.
• Own revenue reporting — a single source of truth for the CRO and executive team on pipeline, bookings, and attainment.
• Run the forecast process end to end: stage-exit criteria, conditional close rates, and a cadence where managers commit their own numbers.
• Build and lead a weekly Demand Council cadence.
• Instrument competitive-presence tracking across the pipeline.
• Partner with the CRO & other members of the executive team on territory design, quota setting and modeling, and compensation plan mechanics.

AI in the Revenue Stack:

• Evaluate, select, and land AI tooling into the GTM stack. The bar is judgment and change management — landing something reps actually use — not necessarily building it in-house.
• Drive adoption of what gets deployed, with usage data to show it changed behavior, not just that it shipped.
• Be personally hands-on with the tools, not just directing a team that uses them — baseline Salesforce administrator fluency, plus firsthand experience connecting AI directly to the CRM (e.g., using Claude via MCP against Salesforce), not just vendor evaluation.
• Operate credibly on both sides of the point-solution question, by design: able to work within and get real value out of an existing vendor stack (Domo, Terret-style tools) and able to design and land an AI-native replacement when that's the better call. The seat is not hired to pre-commit to either philosophy — it's hired to have the judgment and the hands to execute whichever one a given problem actually needs.

Cross-Functional Execution:

• Drive initiatives across Sales, Marketing, and Finance without needing to own every function touched.
• Turn diagnosis into action: interventions that reach the field, with a measurable before-and-after.

Team Leadership:

• Build and lead the RevOps team — hiring, developing, and setting priorities as it scales with the company.

Ideal Candidate Competencies

• Can translate a business question into a data model — and defend that model when a sales leader disagrees with it.
• Has served as strategic advisor to a revenue leader — sat at the table for the decision, not just delivered the readout.
• Track record of putting net-new corrective actions into a field sales organization, with a before-and-after.
• Has built a bottoms-up capacity or quota model and personally defended it against a top-down target.
• Forecast discipline — can describe how they'd know the forecast was wrong before the quarter ended.
• Has selected and landed AI tooling that changed how a field team works, backed by adoption data — vendor fluency alone is a disqualifier, not a qualification.
• Has driven cross-organizational initiatives (Sales, Marketing, Finance) without owning every function involved.
• Can describe how the GTM tool stack's data actually connects, not just list the vendors in it.
• Comfortable operating hands-on at Litify's scale (~200 people) — has personally built models, not only managed analysts who did.
• Has a tinkering mindset — experience leveraging expected baseline Salesforce admin credentials to wire AI (e.g. Claude via MCP) directly into Salesforce.
• Has both a considered view and a track record on each side of the point-solution question — can point to a time they got real value working inside a vendor stack, and a time they consolidated one away in favor of an AI-native workflow. Screened on versatility, not on which side they favor.

Disclosure:
The estimated base salary range for this role is $175,000-190,000. You will also be offered a bonus and benefits.

Our salary ranges are based on paying competitively for our size and industry, and are one part of many compensation, benefits and other reward opportunities we provide.

Individual pay rate decisions are based on a number of factors, including qualifications for the role, experience level, skill set, and balancing internal equity relative to peers at the company.