Job description
About the Role
Join a fast-moving, seed-stage AI infrastructure company building the communication and identity layer for AI agents. As a GTM Engineer, you will architect the systems behind the company's growth — owning the data pipeline, outbound engine, and the company-wide source of truth from day one. This is a high-agency, build-and-own role for someone who wants to help invent a market, not just run someone else's playbook.
The product is an API-first email infrastructure platform purpose-built for AI agents — enabling them to send, receive, and manage email programmatically. The company is backed by top-tier investors and growing quickly in the developer tools and AI infrastructure space.
What You'll Do
Own the growth data layer end to end: instrument the funnel, enrich every signup, and build dashboards that serve as the company's source of truth.
Turn top customers into ten more through lookalike modeling, automated outbound, LinkedIn plays, and surfacing champions inside existing accounts.
Run experiments across the PLG engine — content, integrations, backlinks, paid — and double down on what drives signups.
Connect the GTM stack through APIs, webhooks, and automation so data flows cleanly between analytics platforms, CRMs, enrichment providers, and outbound tooling.
Own tooling decisions: evaluate, adopt, and retire tools as the stack evolves.
Build AI-powered internal tools and ship systems from prototype through rollout, adoption, and governance.
What We're Looking For
Required
3+ years of experience as a GTM Engineer, Sales Engineer, or similar customer-facing technical role building and delivering solutions.
Proficiency in at least one programming language (Python, TypeScript/JavaScript, SQL, or similar) demonstrated through production code or real projects.
Solid technical foundation in CS, data science, or equivalent — you write real scripts, wire APIs together, and are comfortable with modern AI coding tools.
Hands-on experience designing, instrumenting, and owning a growth data layer and the dashboards that serve as a company's source of truth.
Experience building and maintaining data pipelines that move data between analytics platforms, CRMs, enrichment providers, and outbound tools via APIs and webhooks.
Experience running PLG growth experiments — A/B testing, content, integrations, backlinks, paid channels, and lookalike modeling for outbound.
Ability to ship AI-powered internal tools from prototype through full rollout with adoption and governance.
Experience with API design, REST/GraphQL, or integration patterns.
Experience with cloud platforms (AWS, GCP, or Azure) and/or containerization (Docker, Kubernetes).
Experience with SQL databases and data querying.
Comfortable with Git and collaborative development workflows.
High agency in ambiguity: you call out what's broken, form an opinion, and fix things without being asked.
Organized enough that the systems you build don't rot — clean data is a discipline, not a feature.
Able to work on-site in San Francisco, Los Angeles, or New York City.
Bonus / Nice to Have
Hands-on experience with Clay, n8n, enrichment waterfalls, or email sending infrastructure.
PostHog fluency.
Experience shipping agentic workflows or internal AI tooling.
Background at a technical PLG company.
Experience with infrastructure-as-code or DevOps tooling.
Experience with monitoring, logging, or observability tools.
Compensation & Benefits
Salary: $120,000 – $200,000 USD annually, depending on experience.
Early-stage equity in a well-backed company at the ground floor of the AI agent communication market.
Visa sponsorship is not available for this role.
Location
This is a fully on-site role. Candidates must be willing and able to work in person at one of the following offices: San Francisco, CA · Los Angeles, CA · New York City, NY.
Originally posted on Himalayas
Who can apply
Eligible countries: United States. Accepted UTC offsets: UTC-10, UTC-9, UTC-8, UTC-7, UTC-6, UTC-5, UTC+14. Review the full description for employer-specific work authorization, residency and schedule requirements.