Founding Engineer
Inventure
San Francisco, CA0–5 yrs1h agovia LinkedIn
This job at a glance
- Who can apply
- New grads and up to 5 years
- Must know
- LLMsOperationsPythonTypeScriptPostgreSQLMachine learning
- Work
- On-site in San Francisco
- Pay
- Not stated by the employer.
- Skill demand
- Python35%Operations26%LLMs25%TypeScript15%of 99 similar entry-level jobs posted in the US this week
- Listed
- Nov 11, 2026 · still open
Sign in free to see which of these skills your resume already shows.
About the Role
Inventure is partnering with an AI-native startup that is rebuilding how wholesale distribution operates. The company is building an AI-powered distributor that uses LLMs to buy and sell inventory, replacing traditional methods like email and PDFs. They have secured $20M in inception funding led by Kleiner Perkins. This is a founding engineer role on a small, in-person team, offering significant ownership and the opportunity to own an entire problem domain from the outset.
Key Responsibilities
- Own an entire problem domain (e.g., purchase-order lifecycle, entity resolution, agentic search).
- Write substantial code across backend, systems, and product.
- Build on a durable-execution platform running fleets of agents.
- Transact for real using Python, TypeScript, Postgres, and LLMs.
- Speak directly with buyers and suppliers, and translate learnings into shipped product.
- Help set the engineering bar and culture as one of the first engineers.
Requirements & Tech Stack
- Generalist software engineer with strong CS fundamentals.
- Track record of shipping.
- Python
- TypeScript
- Postgres
- LLMs
Qualifications
- Demonstrated clear, fast growth, evidenced by:
- A strong early run at a respected engineering company, followed by a move into a founding engineer or founder role at a startup with real traction.
- OR 2–3 years of career progression since graduating from a top CS program (e.g., MIT, Stanford, CMU, Berkeley, UIUC, Cornell, Waterloo, IIT).
- Autonomous and hungry, seeking seed-stage intensity.
- Personable, capable of engaging with customers.
- Remarkable in some way, signaling top-tier ability.
- Backgrounds focused mainly on data engineering, ML research, or solutions work are less likely to fit.
Bonus
- Experience at a prominent AI company or fast-moving early-stage startup (e.g., OpenAI, Anthropic, Cursor, Decagon, Sierra, Cognition, Harvey).
Practicalities
- On-site in San Francisco, five days a week.
- Relocation supported; open to visa transfers and new sponsorship (including H-1B and TN).
- The interview process involves a short chat with the Head of Engineering, a 60-minute live coding round (no AI tools), and a four-hour onsite covering coding, a product case study, and a deep dive into a past project.
- The company moves quickly, with potential for offers within hours.