GTM Engineering Lead

About the role

• ReadyOn.AI is an AI-native Labor Operating System born out of a Stanford AI Lab. It applies AI and market-design principles to matching the world's 2.7 billion frontline workers to the right shifts in real time.
• The platform predicts workforce demand, dynamically matches it to an employer's employee supply, and automates staffing decisions across complex, multi-site operations. It aims to give workers flexibility and autonomy while helping employers meet labor-cost targets.
• Frontline labor often represents 40% of an enterprise's P&L. ReadyOn addresses a $3 trillion market historically served by static scheduling software and manual processes, treating staffing as real-time supply–demand orchestration rather than a scheduling problem.
• Customers include a Fortune 250 food-service enterprise with 300,000 employees across 16 countries and more than $7 billion in annual labor spend; a Fortune 500 hotel group with more than 250,000 employees and over $5 billion in annual labor spend; and a Fortune 250 entertainment operator with 75,000 employees and more than $4 billion in labor spend.
• Headquartered in San Francisco with 80 employees, ReadyOn reported 8x year-over-year revenue growth in 2025, driven by multiple seven-figure Fortune 250 enterprise deployments and an expanding pipeline. It has multiple multimillion-dollar customers, consistent expansion within existing accounts, and measurable ROI.
• AI is central to the platform: demand forecasting and shift assignment flow through an adaptive, autonomous decision layer that learns from operational data and optimizes cost, compliance, and worker satisfaction.
• The founding team includes Reza, an engineering leader who scaled enterprise systems at Google, Yahoo, and AT&T; Dominic, an operator who optimized labor-intensive operations in 21 countries; and Mohammad, a Stanford professor and expert in algorithmic market design.
• Reporting to the Head of Marketing, the GTM Engineering Lead will build and run the automated engine that turns account signals into first meetings with the world's largest frontline employers.
• Own the systems behind outbound and inbound motions, including readiness signals, enrichment, messaging, and the handoff that puts qualified meetings on sellers' calendars.
• Work daily with Marketing and closely with Sales, RevOps, and Security, using HubSpot as the system of record and AI throughout. Codify plays into runbooks, templates, and prompts so the team can scale what works.

Responsibilities

• Build standing feeds for signals relevant to frontline employers, including new facilities, new general managers, labor pressure, incumbent systems, bargaining activity, earnings calls, and trade press. Score signals and route the strongest into automated plays that take target accounts through to live sequences without manual steps.
• Manage account, contact, and persona tables in Clay. Use Claude and Clay to generate personalized messages from Marketing's core messaging.
• Launch one-touch, multi-touch, and nurture campaigns across email and LinkedIn using tools such as Apollo, HeyReach, and HubSpot. Build webinar and inbound plays covering site tracking, form routing, and sequences for attendees, no-shows, and demo sign-ups.
• Own deliverability, including sending domains, mailboxes, warmup, verification, and automated send screening to prevent messages from reaching the wrong people.
• Build routing, suppression, and handoff workflows so every positive reply reaches the correct owner the same day with a task and alert. Remove contacts from sequences when they reply or book.
• Maintain HubSpot campaign lists, tags, and fields under shared naming conventions. Keep incoming data clean and deal fields current through automation. Partner with RevOps on every field, workflow, and sync change, and support administration and reporting when needed.
• Review campaign-level results in HubSpot with Sales to decide which plays and signals to scale or retire.
• Automate research, list building, and first touches previously performed manually by BDRs. Build research and campaign-analysis agents on ReadyOn data within security rules, and document every play, template, prompt, and sequence in reusable runbooks.
• As the role grows, own GTM architecture across outbound, inbound, nurture, and Sales handoffs, and define the data model with RevOps.
• Test which signals predict meetings, add new sources, and retire ineffective ones. Build agents that run plays end to end with evaluations and security-approved guardrails.
• Take ownership of qualified pipeline generated by the engine, using experiments to shape the plan.
• Manage contractors, grow a small GTM engineering team, and partner with a RevOps leader as the organization expands.
• Set quarterly GTM plans with Marketing and Sales and establish new motions, such as new verticals or partner channels.

Requirements

• At least 3 years of experience in GTM engineering, growth, marketing operations, or revenue operations at high-growth B2B software companies.
• Demonstrated experience building signal-to-sequence systems in tools such as Clay, Apollo, HeyReach, HubSpot, and n8n, with the ability to explain the work.
• Daily use of large language models and agents, including Claude, Clay's AI steps, and connected tools, with examples of what you have built.
• Comfort with enrichment, data modeling, and deduplication. SQL or advanced spreadsheet skills are a plus.
• Knowledge of healthy sending practices, including email verification, suppression, and opt-outs.
• Experience supporting long-cycle enterprise sales involving buying committees and multiple personas per account.
• Strong interest or experience in labor operations or workforce management is a significant advantage.
• Experience co-owning a CRM with Sales, including HubSpot administration and reporting, is a nice-to-have.
• A builder-first mindset: ship working plays quickly and turn rough briefs and raw account lists into live sequences.
• Prioritize meaningful reasons to reach out, such as a new property, a new general manager, or rising labor pressure, and set clear standards for actionable signals.
• Use AI for research, writing, and routing at scale while knowing where human review is necessary.
• Move quickly without compromising shared systems: log changes and seek approval before changing shared data.
• Be willing to perform manual work to validate a play, then automate it so the team can scale.
• Measure success by meetings sellers want to take and give handoffs as much attention as outreach.