GTM Engineer

Revenue Operations

At Justworks, we're building the infrastructure that helps small businesses run, payroll, benefits, compliance, and HR in one place. We're data-driven, move with urgency, and care deeply about the people on our team and the customers we serve. If you want to build things that matter inside a company with real scale and real complexity, you'll fit right in.

You care about shipping things that change how revenue teams operate — not just automating tasks, but architecting the systems underneath them. You’ve built things in production. You think in systems. You’ve worked with LLMs not as a novelty but as a primitive you compose with, the same way you’d reach for a database or a queue.

You understand that the next generation of GTM infrastructure isn't a better Salesforce configuration or a smarter Zapier flow — it's a unified, AI-native application layer that gives sellers, CS reps, and revenue leaders a single surface to execute, coach, and decide. You want to build that at Justworks.

This role sits inside Revenue Operations. You'll work closely with Sales, Customer Success, RevOps, and Data & Analytics to identify high-leverage problems and ship solutions that stick.

• Internal GTM Applications: Design, develop, and own production-grade internal tools — seller intelligence dashboards, deal briefing surfaces, renewal risk consoles, CS health views — built on top of Justworks' GTM data stack (Salesforce, Snowflake, Gong, Zendesk). These aren't prototype demos. They're applications with real users, real uptime requirements, and real business impact.
• API & MCP Integration Layer: Stitch together the GTM tech stack into coherent application experiences. You'll be writing against Salesforce APIs, Gong APIs, Snowflake, and increasingly against MCP-enabled tools — creating a composable, unified data layer sellers and operators actually want to use.
• LLM Powered Workflows: Identify the highest-leverage places to embed AI in the revenue motion — deal risk detection, call summarization, next-best-action recommendations, automated pipeline commentary — and ship them as features, not experiments. You design these to be self-reporting: measurable, attributable, and improvable over time.
• Data Pipelines in Support of GTM Intelligence: Partner with Data & Analytics to extend and maintain ELT pipelines that power GTM tooling — building from Salesforce, Gong, and Zendesk into Snowflake with the reliability a revenue team depends on.
• Rapid Prototyping to Production: Move from problem statement to working prototype to shipped feature fast. You're not the person who spends six months scoping. You build, get feedback, and iterate.

You'll embed directly with revenue leadership and front-line teams to understand where friction lives. You'll own problems end-to-end — from discovery through deployment and instrumentation. You'll communicate tradeoffs clearly, build for maintainability, and ship with the urgency of someone who knows that slow tooling costs quota. All team members focus on aligning their behaviors to our core values:

• Camaraderie – You work collaboratively toward shared goals and support teammates across functions
• Openness – You default to transparency and bring curiosity to every conversation
• Grit – You take pride in getting the details right while maintaining a bias toward action
• Integrity – You hold yourself accountable to do what you say and communicate proactively
• Simplicity – You design systems and workflows that are effective, streamlined, and easy to understand

• 4+ years of experience building and shipping production applications — backend services, internal tools, or data-intensive systems
• Strong Python and/or JavaScript/TypeScript fluency; you write code you're comfortable defending in a review
• Demonstrated experience building LLM-powered features or applications using APIs (OpenAI, Anthropic, etc.) — prompt engineering, RAG, tool use/function calling, agent patterns
• Experience integrating APIs across enterprise systems (Salesforce, Gong, or equivalent GTM tooling)
• SQL fluency; comfort working with Snowflake or similar cloud data warehouses
• Ability to go from a vague business problem to a scoped technical solution without hand-holding

• Experience with MCP (Model Context Protocol) or agentic AI architectures
• Background building internal tools or developer-facing products
• Familiarity with Flask, FastAPI, or lightweight backend frameworks for hosting internal apps
• Cloud deployment experience (GCP, AWS, or Azure — containerized apps, Cloud Run, etc.)
• Prior experience working inside a GTM or RevOps function, or closely embedded with one
• Former founder or early-stage startup engineer who built something from zero to users

The base wage range for this position based in our New York City Office is targeted at $112,500.00 - $123,750.00 per year.

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