Founding Engineer, Agent and Data Systems
Required skills
- LLM
- agent systems
- tool-use loops
- evidence-driven learning systems
- replay and simulation infrastructure
- evaluation and promotion gates
- backend systems
- orchestration
- state
- versioning
Nice to have
- data engineering experience
Role summary
Tenor is a seed-stage startup building full-stack infrastructure for AI-native businesses. They are hiring a Founding Engineer to take end-to-end ownership across agent, data, backend, and product systems. This role involves engineering agent harnesses, tool-use loops, evidence-driven learning systems, replay and simulation infrastructure, evaluation and promotion gates, and the backend and full-stack product systems. The engineer will work directly with founders to develop reliable product infrastructure and shape technical architecture and product. The ideal candidate has concrete experience building and operating LLM-driven agent systems, strong backend and systems engineering fundamentals, and full-stack product instincts. Data engineering experience is a plus. High agency and ownership are crucial for this role, which is based in San Francisco.
Tenor (YC S26) is building the full-stack infrastructure for AI-native businesses, redefining how companies are built, launched, and scaled in the 21st century. We're a four-person, seed-stage startup hiring our fifth teammate. Our team brings together engineering, ML, and product experience from Tesla, Waymo, Amazon, UC Berkeley, and Stanford, including research published at ICML.
The role
We are hiring a founding engineer with end-to-end ownership across agent, data, backend, and product systems. You will engineer harnesses across our agent systems, including tool-use loops, evidence-driven learning systems, replay and simulation infrastructure, evaluation and promotion gates, and the backend and full-stack product systems that hold everything together.
You will work directly with the founders to turn prototypes into reliable product infrastructure and shape both the technical architecture and the product.
What you will have ownership in
• Design and operate reliable agent harnesses, execution systems, replay and simulation infrastructure, and evaluation and promotion gates.
• Build backend systems for orchestration, state, versioning, observability, and reliability.
• Build data systems, including pipelines, ETL, data modeling, and warehousing.
• Ship full-stack product features across APIs, services, and user-facing workflows.
• Work closely with customers and the founding team to identify problems, test ideas, and ship quickly.
What we are looking for
• Concrete evidence of building and operating LLM-driven agent systems, beyond calling a chat API.
• Hands-on harness engineering experience, including tool execution, evals, replay, simulation, state, and observability.
• Strong backend and systems engineering fundamentals.
• Full-stack product instincts and the ability to work wherever the product needs you.
• Data engineering experience with pipelines, ETL, modeling, or warehousing is a meaningful advantage.
• High agency and ownership. You start, ship, and improve things without waiting for detailed direction.
• Comfort with the pace and ambiguity of a very early-stage startup.
We care more about demonstrated ability than years of experience. Strong side projects, open-source work, publications, internships, or startup experience can all be compelling when they show relevant outcomes.
Location and compensation
This is a full-time, in-person role in San Francisco. We support relocation and US visa sponsorship. The base salary is $150,000 to $200,000, plus 0.5% to 1.5% equity.
Similar roles
Founding Engineer - FrontendVantheon · Austin, TX · Onsite- Founding Engineer at HeaviAICox Exponential · San Francisco, CA · Onsite
- Founding EngineerValent Procure · New York, NY · Onsite
- Founding Engineer, TransportationCorgi Insurance · Boston, MA · Onsite
- Founding Engineer (San Francisco, CA)Aglide · San Francisco, CA · Onsite
Founding EngineerUltralytics · New York, NY · Hybrid
