Bluejay

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GTM Engineer

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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 systems—lead gen, enrichment, scoring, AI-native workflows—that 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 leverage—more 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 builds—part 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 world—AI agents, evals, observability—well enough to build systems that target the right buyers.
  • Outcome bias. You measure pipeline created and rep efficiency gained, not dashboards built.
  • Comfort with ambiguity—you're building the systems from zero, not maintaining someone else's.

Core Traits

  • Builder instincts—you 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

This is for someone who wants to engineer how Bluejay grows.

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.

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