SlipstreamJobs tracks this role from the company's public career site. Apply directly on the employer's site.
Salary: USD 120,000 - 130,000 / annual
Soda is the data quality layer for Fortune 500 companies like Disney, Ralph Lauren, CBRE, and HelloFresh. The company is hiring one person to own content end-to-end: website, technical blogs, webinars, product videos, and personal audience building.
This is a hybrid role combining technical writing, growth engineering, and content strategy. The core challenge: most expertise exists in the heads of founders and customer engineers but rarely gets published. Your job is to extract that knowledge and scale it through AI-powered content systems—not hand-crafted pieces, but a machine that produces high-quality, distinct-voiced content at volume.
You'll report to a co-founder and work within the Growth team. The role requires both writing and building: you'll write code daily (Python/TypeScript, APIs, webhooks, databases) to create multi-step LLM pipelines with structured outputs and evals. You'll use agentic workflows (Claude Code, MCP servers, agent skills) as your daily toolkit. The bar is taste and anti-slop: you must be able to recognize and reject lifeless output, diagnose why the pipeline failed, and fix it. Your own profile and following serve as proof the system works.
This is not a traditional software engineering role, DevRel circuit, or marketing operations job. It's a specialized hybrid for someone who can write credibly for technical audiences (Staff Data Engineers, CDOs), build autonomously, and think like a generalist problem-solver.
**Requirements:**
- Demonstrated writing ability: must provide a sample of technical writing that a technical audience actually read (non-negotiable)
- Serious prompt engineering: multi-step LLM pipelines with structured outputs and evals; understanding of why naive approaches produce poor output
- 3+ years building things that go to market: technical content, growth engineering, marketing engineering, GTM engineering, DevRel, marketing ops, RevOps, or founder background
- Autonomous coding ability: Python or TypeScript, APIs, webhooks, databases; nothing should be blocked waiting for an engineer
- Data fluency: credible understanding of pipelines, data quality, and data warehouses to write for data engineering audiences
- Generalist instinct: identify constraints and fix them; prefer building workflows to repetitive tasks
- Independence: thrive in distributed, async teams across 12+ countries without hand-holding
- Fluent English
**Good to have:**
- Grown a technical audience (newsletter, blog, LinkedIn, open source, YouTube)
- Content, growth, or DevRel experience in data, developer tools, or infrastructure
- Shipped agentic workflows to real users (MCP servers, Claude skills, tool-using agents)
- Video production and editing skills
- Data quality, data management, or data observability industry experience
