Soda is the data quality layer for Disney, Ralph Lauren, CBRE, HelloFresh, 2K Games, and Nubank. The category is growing rapidly because AI doesn't work on bad data.
We're hiring a GTM Engineer to build the machinery that gets that message to the people who need it. You'll join the Growth team reporting to a co-founder, and build the systems the rest of the team runs on: content, visuals, videos, skills, agents- whatever the biggest constraint is that quarter. Your first and largest project is the content engine.
RequirementsWe publish a lot - webinars, technical blogs, founder LinkedIn, product marketing - and most of it is still hand-made. Your job is to build a pipeline that turns a raw source into content a Staff Data Engineer or CDO with 20 years of experience would read and forward: real prompt engineering, a defined voice per author, evals that catch regressions, and the taste to kill output that's accurate and lifeless. Anti-slop is the point: an engine that ships slop faster has negative value. We build agentically here - Claude Code, MCP servers, and agent skills are the daily workflow.
What You'll Do- Build the content engine end-to-end: ingestion, theme extraction, drafting, evals, and the review step
- Create content including webinars and product videos
- Own and grow audience
- Our team writes in distinct ways; the engine should sound like them, not like a model.
- Make quality measurable.
- Own the numbers - reach, engagement, pipeline influence - and cut what doesn't work.
- Contribute the rest of the Growth stack as constraints move.
- Work directly with the founders, customers, customer engineers, to lean and improve on how Soda talks about the category. Your opinion matters here.
You Should Have- 3+ years building things that go to market: growth engineering, marketing ops, technical content, RevOps, or a founder background. Titles vary; portfolios don't.
- You can write, story tell, and you can tell good writing from bad: send us something you wrote that a technical audience read. The most important line in this ad.
- Serious prompt engineering: multi-step LLM pipelines with structured outputs and evals, not chatting with a model. You know why the naive version produces slop.
- Enough code to be autonomous: Python or TypeScript, APIs, webhooks, a database. Nothing should be blocked waiting for an engineer.
- Generalist instinct: you find the constraint and fix it, and you'd rather build the workflow than do the task fifteen more times.
- Enough data fluency to be credible: you can hold your own on pipelines, dbt, and warehouses.
- Independence: you don't need hand-holding in a distributed, async team across 12+ countries.
- Fluent English.
Good to Have- Marketing or growth in data, developer tools, or infrastructure.
- You've grown a technical audience of your own: newsletter, blog, LinkedIn, open source.
- Building agentic workflows: MCP servers, Claude skills, or tool-using agents shipped to real users.
- Data quality, data management, or data observability industry experience.
Benefits- $120,000-$130,000 base salary + equity.
- Fully remote (US-based), with our Brooklyn office available if you want one.
- All the tokens you need, across all frontier models.
- Real ownership, real impact, no micromanagement.
- PTO, 401k, medical insurance.
😡 What you might not love- Rapidly changing priorities: our roadmap can pivot quickly. It's a fast-paced environment with a LOT of work to be done.
- New and broad: no playbook for this role yet, and you'll be judged on output, not architecture. An elegant pipeline nobody reads from is a failure.
Hiring Process- Screening - send one piece of writing or video you're proud of, and one thing you've built with AI.
- 20-minute phone screen - with a founder
- Craft deep dive (90 min)
- Culture fit (1 hour)
We answer every application, and every candidate hears back within 3-5 days of each step. If it's not a hell yes, it's a no, and we'll tell you quickly and kindly.
