Senior Software Engineer - Former founder preferred

About the Role

Consumer packaged goods like sauce, cookie, and lotion are used by every single human on the planet. Developing these products is hard, manual, and complex. Turing solves this by purpose‑built AI to discover the most optimal formulation, replacing decades of trial‑and‑error. Your code will run inside the R&D pipelines of some of the largest CPG companies on the planet — billion‑dollar brands whose products are on shelves in every country.

Why This Is Hard (and Interesting)

We are building a product experience that translates ambiguous, highly complex, subjective matter expertise, and physical chemistry needs into solutions for users who never had better tools than spreadsheets. This requires going far beyond traditional statistical methods and basic LLM calls. You will own the end‑to‑end development of AI‑powered features across the backend, frontend, and deployment layers. You will build on our proprietary ML algorithms, LLMs, internal embeddings, and structured data models into product experiences that users actually trust. This is a zero‑to‑one build. You will ideate, plan, and deliver software that consistently exceeds customer expectations.

Team & Culture

We are backed by $19.75M in funding from Y Combinator, Insight Partners, and elite angels like Eric Ries. We operate with a high‑agency culture:

• Customer Value: We talk less and ship something very fast that customers can see and use.
• Direct Customer Interaction: Engineers talk directly to customers; there is no translation layer or PM shielding.
• Fast Decision Making: We debate on Monday, decide immediately, and execute quickly.
• Results Over Process: We care about customer impact, not performative engineering practices.

We are a small, elite team in the Bay Area, working six days a week (Sundays off) to win.

We Should Talk If You’re

• You are a 100x AI‑Native Engineer who wields AI coding tools (Claude Code, Codex, etc.) to act as a force multiplier and ship at an impossible speed, constantly rethinking processes to stay at the bleeding edge.
• You’re a skilled engineer with the experience, judgement, and skillset to architect and implement the backbone of a modern AI‑native SaaS product.
• Previously a founder or founding engineer who has built something from scratch that people use or pay for.
• You’re unusually obsessed with hard problems and are willing to go all‑in to accomplish any goal you set.
• You’re comfortable with ambiguity and adapting to dynamic priorities, with good judgement to manage fires.
• You have excellent communication and candor, communicating directly with customers, users, engineers, and collaborating on key decisions.
• You’re self‑motivated to solve bigger problems, not just a pay‑me‑to‑perform type person.
• You have grit and perseverance, accustomed to picking between hard options and pushing through.

What You’ll Do

We are looking for someone who has shipped real things in hard domains, has genuine depth with LLM and ML integration (not just API calls), and has used AI coding tools as a multiplier, not a crutch. If you have built a product end‑to‑end — backend, frontend, deployment — and have strong opinions about how to do it well, we want to talk. Experience with vertical SaaS, internal tools, ML/analytics platforms, or enterprise software is a strong signal, as is having been a founder or taking extreme ownership in an early‑stage environment.

What You Bring

• Deep experience integrating LLMs and ML into products (e.g., LangChain, vector DBs, prompt design, model outputs).
• A track record of shipping real products, ideally in vertical SaaS, internal tools, ML/analytics platforms, or enterprise software.
• The ability to think in product, understanding UX, user value, and workflows, not just write code.
• A strong desire to work in‑person as an individual contributor with a small team to move fast and win together.

Must‑Haves

• 5+ years of full‑stack or backend‑heavy engineering experience.
• LLM and/or ML integration experience (e.g., LangChain, vector DBs, prompt design, model outputs).
• Shipped real products, ideally in vertical SaaS, internal tools, ML/analytics platforms, or enterprise software.
• Strong product mindset: UX, value, users.
• Founder experience or extreme ownership in a startup.
• Willingness to work in‑person with a small team to win together.