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Product Manager, AI Infrastructure

typesafe ai • United State
Visa Sponsorship
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Shape the product direction and user experience of Jev, a machine-native intelligence infrastructure for automation. Translate evolving frontier AI model capabilities into compelling product experiences for developers and users. Requires strong technical intuition and a proven track record of shipping technical products from 0 to 1.

Key Highlights
Define an exciting new AI product from the ground up in a fast-moving, ambiguous environment.
Work closely with the CEO and engineering teams to bring frontier AI capabilities to production.
Significant ownership and influence over both the product and the internal build processes.
Key Responsibilities
Translate rapidly evolving model capabilities into compelling product experiences.
Identify what to build next and drive execution from early ideas through launch and iteration.
Collaborate with engineering teams on architecture, tradeoffs, and product decisions.
Analyze usage data and talk to developers to ship continuous improvements.
Turn user feedback into clear priorities and product requirements.
Technical Skills Required
Product Management API Design Technical Product Strategy
Benefits & Perks
Base salary of $150k–250k
Equity
100% covered health insurance
Daily lunch and dinner
Visa sponsorships
401K plans
Nice to Have
Previous experience building products specifically for developers
5+ years of product management experience building highly technical products
Experience scaling products from 0 to 1
Experience building developer-facing products, APIs, or infrastructure tools

Job Description

TypeSafe AI is an AI lab building machine-native intelligence infrastructure for automation, designed to make decisions within software by combining the intelligence of LLMs with the efficiency and reliability of code into a new shape of AI: System One Models. Based in San Francisco, TypeSafe AI recently launched its first public model, Jev.While others chase benchmarks and academic puzzles, we’ve been quietly rethinking the LLM stack from first principles — building a new kind of general frontier model designed for real-world reliability, decision-making, and autonomy in production.
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