/roles — ROLE_268
Senior Backend Engineer
Seed-stage company applying AI to how consumer goods brands buy ingredients and packaging
The role
- COMP
- $200K - $235K
- EQUITY
- Competitive equity
- LOCATION
- San Francisco · South Bay Area
- WORKPLACE
- On-site
- EXPERIENCE
- 6 - 12 years
- VISA
- None, Visa transfers
- STACK
- TypeScript, NodeJS, React, GraphQL, PostgreSQL, AWS
- INDUSTRY
- AI, B2B, Enterprise, Consumer, Logistics, Manufacturing
The company
Seed-stage AI company building procurement software for consumer goods (CPG) brands, turning scattered supplier emails, PDFs, and spreadsheets into structured data and better buying decisions.
- STAGE
- Series A-stage
- FUNDING
- $9M raised
- TEAM
- ~10 people
- FOUNDED
- 2024
JD — the work
About the role
You would be the go-to owner of backend design, data infrastructure, and scaling as an AI procurement platform for consumer goods brands grows. That covers database schemas, large migrations, and async queueing, while you spend roughly 40 to 50% of your time building customer-facing product. The team is small, fast, and still searching for product-market fit, so expect to test ideas quickly and sometimes throw code away.
What you'll do
- Set backend architecture: schema design, API conventions, and big migrations run against production customer data
- Move heavy writes off the database path and onto queue-based asynchronous processing that can handle rising volume
- Establish conventions and mentor teammates on architecture and design tradeoffs
- Spend roughly 40 to 50% of your time shipping customer-facing features and iterating on feedback
- Use coding agents every day, orchestrating loops, worktrees, and multiple agents to move faster
What they're looking for
- 6+ years building production systems, deep on the backend and data side: schemas, migrations, queues, APIs
- At least 2 years at an early startup (Series A stage or before), comfortable with ambiguity, speed, and throwaway code
- Talks about impact in terms of customer problems solved rather than tools used, and communicates clearly in writing and aloud
- Daily hands-on use of coding agents, well beyond autocomplete
- Background building B2B apps, plus some exposure to messy unstructured inputs or growth-related scaling problems
- Comfort with TypeScript, Node.js, GraphQL, and PostgreSQL on AWS