GTM Engineer

GTM Engineer

Bluejay is building the simulation, evaluation, and observability layer for voice + text AI agents. We work with Fortune 500s, multinational corporations, and high-growth startups to ensure their AI agents actually perform as intended in production. We raised a $4M seed backed by Floodgate, Peak XV, and YC.

Now we're looking for a cracked GTM engineer to treat go-to-market like an engineering problem. We don't want someone to "run a sequence tool." We want someone who builds the automated systemslead gen, enrichment, scoring, AI-native workflowsthat make every rep on the team a force multiplier.

What You'll Actually Be Doing

You'll build and own the machinery behind pipeline: the data, the automations, the AI-native workflows, and the tooling that makes outbound and revenue scale.

Build the GTM Engine

• Design and build scalable lead-gen systems using enrichment, automation, and AI
• Build LLM-powered workflows: personalized outbound, signal detection, lead scoring, research
• Wire together the stack (Clay, n8n/Zapier, CRM, APIs, scripts) into systems that actually run
• Treat outbound like a product: instrument it, measure it, refine it

Own the Data & Tooling

• Build and maintain clean, enriched lead lists and account data
• Architect the CRM and keep the pipeline honest and queryable
• Build dashboards and reporting so the team sees what's working and why
• Automate the manual work that's slowing reps down

Force-Multiply the Team

• Give the SDR, AE, and Founding GTM leveragemore pipeline, better targeting, less busywork
• Spot bottlenecks in the funnel and engineer them away
• Constantly experiment with new tools, tactics, and growth mechanics

You Will Be

• Building
• Automating
• Instrumenting
• Iterating
• In the trenches with founders and the GTM team

This is a founding-level ownership role, not a "manage the tools" seat. You're building the systems the whole revenue org runs on.

Who You Are

We're looking for a hustler who buildspart operator, part engineer. Titles matter less than what you've shipped.

Must-Haves

• Technical and hands-on. You're comfortable with APIs, scripts, SQL, and modern GTM tooling (Clay, n8n, Zapier, or similar). You can build, not just configure.
• AI-native to the core. You build LLM-powered workflows instinctively and reach for automation before manual work.
• You can hold a credible conversation about our worldAI agents, evals, observabilitywell enough to build systems that target the right buyers.
• Outcome bias. You measure pipeline created and rep efficiency gained, not dashboards built.
• Comfort with ambiguityyou're building the systems from zero, not maintaining someone else's.

Core Traits

• Builder instinctsyou see a manual process and itch to automate it
• Scrappy and resourceful
• Gets excited building systems from zero
• Thinks in experiments, not opinions
• Comfortable being wrong quickly

Desirable Quirks

• Physically cringes at manual data entry
• Has strong opinions about enrichment and data quality
• Gets irrationally excited about a clean, automated workflow
• Reads the changelogs of tools they don't even use yet
• Thinks GTM is part code, part growth, part math

Experiences That Pique Our Interest

• Built GTM, RevOps, or growth-engineering systems before
• Background in engineering, data, or technical ops who moved toward GTM
• Built outbound or enrichment automations from scratch
• Worked at an early-stage startup, or founded something technical
• Career-pivot candidates welcome if you can show you've built real systems

What This Is Not

• Not a "just configure the CRM" role
• Not a single-tool admin job
• Not a late-stage, highly specialized position
• Not for someone who needs rigid structure

Logistics

• Full-time, in-office
• You'll work extremely closely with the founders and the GTM team
• Hiring in the next ~2 months, but we'll move fast for someone exceptional

Compensation

• Base: ~$100K$160K, calibrated to experience
• Meaningful early-stage equity
• Performance upside tied to pipeline and efficiency

If you want to engineer the growth systems behind the infrastructure powering AI agents at the largest companies in the world

Let's talk.