Revenue Operations Manager

Overview

You'll run revenue operations for Definely, a 117-person legaltech company selling AI contract tools to law firms and in-house legal teams. This role is about building AI-powered workflows and automation in the revenue stack, not just keeping Salesforce clean. You'll work directly with sales, CS, and product to embed tools like Claude and Gemini into day-to-day GTM operations.

Role Snapshot

Company Context

Stage: Growth stage (117 employees, mature product)

Size: 117 employees

Growth: Hiring for RevOps suggests scaling GTM motion and deal volume

Market Position: Niche player in legal tech AI space - competing against generic contract tools and established legal software

GTM Reality

Who They Sell To:

• BigLaw partners and legal ops leaders at Am Law 200 firms
• General Counsel and legal ops teams at enterprises
• These are risk-averse, consensus-driven buyers with long procurement cycles

GTM Motion:

• Likely heavy outbound to targeted accounts (law firms, F500 legal departments)
• Some inbound from legal tech conferences and word-of-mouth
• Product likely requires demo + proof of value given legal industry conservatism
• Deals probably involve IT security reviews, partner committee approvals, firm-wide rollouts

Sales Structure:

• Probably 10-20 AEs/AMs managing enterprise accounts
• Mix of new logo hunting and account expansion
• Sales cycles likely 3-6+ months given legal industry buying process

What You'll Actually Do

Time Breakdown

AI/Automation Projects (35%) | Data/Reporting (30%) | System Maintenance (20%) | Ad-hoc Requests (15%)

Key Activities

• Building AI-powered workflows: Use Claude or Gemini APIs to automate tasks like enriching lead data, drafting personalized outreach, analyzing call transcripts for deal insights, or generating account research summaries. You're prototyping these workflows, testing them with reps, and productionizing what works.

• Automating insight generation: Instead of manually building sales dashboards, you're building pipelines that automatically surface pipeline risks, flag at-risk renewals, identify upsell opportunities, or predict which deals will close. This means SQL queries, Python scripts, and integrating AI analysis into Slack/email alerts.

• Maintaining the revenue stack: Salesforce admin work still exists - managing fields, building reports, fixing broken automations, handling user requests. Probably 20% of your time is keeping the lights on while you build the future state.

• Supporting GTM planning: Working with leadership on territory design, quota setting, pipeline coverage analysis, and forecasting. You're the data person in the room when strategic decisions get made.

• Vendor evaluation and experimentation: Testing new tools (conversation intelligence, data enrichment, AI SDR assistants) to see what actually improves rep productivity vs. what's just hype.

The Honest Reality

What's Hard

• You're the AI guinea pig: Most companies talk about using AI in RevOps - few actually do it well. You'll spend time on experiments that don't work, dealing with hallucinations in AI outputs, and figuring out what's actually worth automating vs. what sounds cool but wastes time.

• Balancing innovation with keeping things running: Reps still need dashboards updated, Salesforce fields fixed, and data cleaned. You can't spend 100% of your time on AI projects when there's regular RevOps work piling up.

• Selling internal stakeholders on new approaches: Sales leaders and reps may be skeptical of AI-generated insights or automated workflows. You'll need to prove ROI and build trust, not just build cool tools.

• Data quality is still a problem: AI workflows only work if the underlying CRM data is clean. You'll likely spend frustrating time on data hygiene before you can do the fun automation work.

• Legal tech sales complexity: This isn't SaaS with clean pipeline metrics. Deals involve multiple stakeholders, long delays for firm approvals, and renewal cycles tied to fiscal years. Your models need to account for this messiness.

What Success Looks Like

• You've built 3-5 AI-powered workflows that reps actually use daily (not just demos you showed in a meeting)
• Sales leadership is making decisions based on automated insights you've surfaced, not just pulling reports
• You've reduced manual reporting work by 50%+ through automation
• Deal forecast accuracy improves by 10-15% because you're flagging risks earlier
• You've evaluated and implemented 2-3 new tools that measurably improve productivity

Who You're Supporting

Primary Internal Customers:

• AEs selling to law firms and corporate legal teams
• Account Managers managing renewals and expansion
• VP/Head of Revenue making strategic GTM decisions

What They Need From You:

• Clean, trustworthy data they can use to prioritize accounts
• Automated workflows that save them time on research and admin
• Insights on what's working/not working in their process
• Fast answers to ad-hoc questions about pipeline, performance, accounts

Requirements

• Experience with Salesforce administration and CRM workflow automation
• Comfort using AI tools (Claude, ChatGPT, Gemini) for data analysis and automation - not just prompting, but actually building workflows
• SQL skills to query data and build custom reports
• Ability to learn new tools quickly and experiment without needing perfect documentation
• Python or similar scripting knowledge is probably required for serious automation work
• Understanding of B2B SaaS metrics (pipeline, conversion rates, velocity, etc.)
• Skeptical, builder mindset - excited to try new things but ruthless about what actually works vs. what's just hype
• Probably 2-4 years in RevOps, sales operations, or analytics roles
• Legal tech or highly regulated industry experience is a plus but not required