Overview
You own the entire revenue org at Path Roboticsâa company selling AI-powered robotic welding cells to manufacturers. You manage sales, customer success, and partnerships, and you're responsible for building repeatable go-to-market processes. You report directly to the CEO and are measured on bookings, expansion revenue, and pipeline predictability.
Role Snapshot
| Aspect | Details |
|---|---|
| Role Type | Chief Revenue Officer |
| Sales Motion | Outbound-heavy, some inbound from word-of-mouth |
| Deal Complexity | Strategic enterprise sales |
| Sales Cycle | 6-12 months |
| Deal Size | $200K-$1M+ per cell installation |
| Quota (est.) | $5-10M+ annual bookings target |
Company Context
Stage: Series B/C stage (185 employees, building out GTM infrastructure)
Size: 185 employees
Growth: Running SKOs, VP of Commercial Ops posting about team culture, actively hiring across GTM roles
Market Position: Category creator in autonomous welding roboticsâselling into a traditional manufacturing market that's skeptical of automation but desperate for welding labor
GTM Reality
Pipeline Sources:
- 70% Outbound - Direct outreach to manufacturers in defense, infrastructure, energy, heavy industry
- 20% Inbound - Word-of-mouth referrals, some conference leads, limited marketing-generated demand
- 10% Partnerships - Integration partners, manufacturing consultants, industry associations
SDR/AE Structure: Small team, likely 3-8 AEs at this stage, possibly adding SDRs or still having AEs self-source
SE Support: Sales Engineers handle technical demos and ROI modelingâcritical for this technical sale
Competitive Landscape
Main Competitors: Traditional manual welding shops, cobots from Universal Robots/ABB/FANUC with manual programming, other robotic welding cell providers
How They Differentiate: AI model (Obsidian) that adapts in real-time to part variations vs. programmed robots that break when parts don't match specs. RaaS model (no capex) vs. $150K+ upfront purchase.
Common Objections: "Our welders won't accept robots," "What happens when parts vary," "We can't afford downtime during implementation," "Our shop floor isn't set up for this"
Win Themes: Labor shortage crisis (can't find welders), 4x productivity vs. manual, consistent quality, 24/7 operation, no capex commitment
What You'll Actually Do
Time Breakdown
Strategic Planning (25%) | Team Development (25%) | Deal Execution (25%) | CEO/Board (15%) | Customer/Market (10%)
Key Activities
- Building the Revenue Playbook: You define ICP, messaging, sales process, pricing strategy. This is still being figured outâwhat works in defense doesn't work in commercial manufacturing.
- Hiring and Developing Leaders: You need to hire a VP of Sales, maybe a VP of Customer Success. You spend time recruiting, onboarding, and coaching them through early deals.
- Strategic Deal Involvement: You join calls with Fortune 500 manufacturers or large defense contractors. You're the closer when deals get stuck or need executive presence.
- CEO/Board Reporting: You build the pipeline model, forecast bookings, present quarterly business reviews. You're defending why deals slipped or pipeline coverage isn't where it needs to be.
- Cross-functional Alignment: You work with Product on customer feedback and roadmap priorities. You work with Operations on deployment capacity and customer onboarding timelines.
The Honest Reality
What's Hard
- Manufacturing is conservative and slow-moving. Deals take 9-12 months and involve convincing multiple stakeholders who've never bought robotics before.
- You're selling a new category. Most buyers don't have budget allocated for "AI welding robots." You're competing with manual labor and fighting skepticism about whether automation really works.
- The sales team is small and might not be fully ramped. You're player-coaching a lotâjumping into deals, writing proposals, doing your own ROI models when needed.
- Implementation is complex. Even after you close a deal, getting the cell installed and running takes months. Customer success issues (slow ramps, production hiccups) reflect back on your org.
- You report to a CEO who's probably technical/product-focused. You need to educate them on why sales cycles are long and why pipeline doesn't convert at 25%.
What Success Looks Like
- You hit $8-12M in bookings your first year and build toward $20M+ run rate
- You hire 2-3 strong sales leaders who can run their teams without you in every deal
- Pipeline becomes predictableâyou can forecast within 15% accuracy
- Customer expansion motion starts working (existing customers add more cells)
- The board stops asking "why is sales taking so long" because you've educated them on the buying process
Who You're Selling To
Primary Buyers:
- VP of Operations or Plant Managers at mid-to-large manufacturers ($50M-$1B+ revenue)
- Head of Engineering or Manufacturing Engineering Directors
- CFOs or procurement leaders (for RaaS contract approvals)
What They Care About:
- Labor availability: Can't find skilled welders, losing institutional knowledge as boomers retire
- Production throughput: Bottlenecks in welding are slowing entire production lines
- Quality consistency: Manual welding quality varies by person and fatigue
- Cost predictability: Fixed monthly cost vs. unpredictable labor + benefits + turnover
- Downtime risk: Will implementation disrupt existing production schedules?
Requirements
- 10+ years in B2B sales leadership, with at least 5 years at VP+ level
- Experience selling complex hardware, capital equipment, or industrial automationâyou need to understand long sales cycles and multi-stakeholder buying committees
- Track record building and scaling revenue teams from $5M to $30M+ ARR
- Comfortable with technical productsâyou don't need to be an engineer, but you need to explain AI/robotics to skeptical manufacturers
- Experience with Robotics-as-a-Service, SaaS, or subscription business models strongly preferred
- Willingness to travel 40%+ to customer sites, tradeshows, and team offsites
- Manufacturing industry experience is a major plus (understand shop floor culture, procurement cycles, implementation complexity)