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Founding Engineer
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Posted 2 months ago
Full Time
San Francisco, California
$170,000 Annually
About the Company
Our client translates real-world workspaces into simulation environments that train expert-level AI agents capable of understanding complex workflows. The company is building reinforcement learning (RL) environments that enable frontier AI labs to develop models that can reason through real operational tasks, not just synthetic benchmarks.
Our client is experiencing rapid adoption, with strong customer pull from leading AI companies and a clear opportunity to become foundational infrastructure for the next generation of intelligent systems.
Why join
- Explosive traction: mid-seven figure ARR with ~200% month-over-month growth
- Direct exposure to frontier AI labs and advanced agent development workflows
- Founding team influence on product direction, architecture, and company culture
- Meaningful equity upside and long-term technical ownership
About the Role
Our client is hiring a Founding Engineer to build core infrastructure that powers RL training environments and agent workflows. This role sits at the intersection of backend engineering, AI infrastructure, and product thinking.
You will work directly with the founders, customers, and domain experts to design systems that translate real-world workflows into environments where AI agents can learn. The ideal candidate enjoys operating in ambiguity, shipping quickly, and taking ownership of systems from idea to production.
This is a high-impact role suited for engineers who want to help define both the technical direction and operating model of an early-stage AI company.
What You Will Do
- Own and deliver core product systems and infrastructure end-to-end
- Design and build RL training environments and supporting backend systems
- Translate customer workflows into structured environments for agent training
- Partner with founders to define technical priorities, architecture, and execution strategy
- Build scalable internal tools to support expert labelers and domain specialists
- Contribute to product direction through rapid iteration and experimentation
- Operate with a product mindset, balancing speed, quality, and usability
- Make foundational decisions that shape long-term platform architecture
Required Skills & Experience
- 2–5 years of experience in backend or fullstack engineering in fast-paced environments
- Strong proficiency in Python
- Experience building production systems (APIs, backend services, data workflows, infrastructure tooling)
- Experience at VC-backed startups (Seed–Series B) OR 1–2 years at a high-caliber big tech company
- Strong communicator able to collaborate across engineering, operations, and customers
- Product-oriented mindset with ability to translate ambiguous requirements into shipped solutions
- Demonstrated ownership of projects end-to-end
- Undergraduate degree in Computer Science or related technical field
Nice to Have
- Experience working with reinforcement learning, machine learning, or model training pipelines
- Familiarity with agent frameworks or evaluation harnesses
- Exposure to data labeling systems, workflow tooling, or human-in-the-loop systems
- Experience working closely with customers to define technical requirements
- Experience at early-stage startups or in founder-like roles
- Comfort operating in fast-changing environments with evolving product requirements
What Does Not Work
- Frontend-leaning engineers without strong backend depth
- Candidates without hands-on experience building production systems
- Profiles focused primarily on research without shipping production software
- Candidates with multiple short tenures indicating limited ownership
- Big tech candidates without evidence of scrappiness or startup-style execution
- Lack of experience working with real-world workflows or operational systems
- Weak communication or inability to clearly explain technical tradeoffs
- Limited exposure to RL environments, agent systems, or infrastructure supporting model training
Our client translates real-world workspaces into simulation environments that train expert-level AI agents capable of understanding complex workflows. The company is building reinforcement learning (RL) environments that enable frontier AI labs to develop models that can reason through real operational tasks, not just synthetic benchmarks.
Our client is experiencing rapid adoption, with strong customer pull from leading AI companies and a clear opportunity to become foundational infrastructure for the next generation of intelligent systems.
Why join
- Explosive traction: mid-seven figure ARR with ~200% month-over-month growth
- Direct exposure to frontier AI labs and advanced agent development workflows
- Founding team influence on product direction, architecture, and company culture
- Meaningful equity upside and long-term technical ownership
About the Role
Our client is hiring a Founding Engineer to build core infrastructure that powers RL training environments and agent workflows. This role sits at the intersection of backend engineering, AI infrastructure, and product thinking.
You will work directly with the founders, customers, and domain experts to design systems that translate real-world workflows into environments where AI agents can learn. The ideal candidate enjoys operating in ambiguity, shipping quickly, and taking ownership of systems from idea to production.
This is a high-impact role suited for engineers who want to help define both the technical direction and operating model of an early-stage AI company.
What You Will Do
- Own and deliver core product systems and infrastructure end-to-end
- Design and build RL training environments and supporting backend systems
- Translate customer workflows into structured environments for agent training
- Partner with founders to define technical priorities, architecture, and execution strategy
- Build scalable internal tools to support expert labelers and domain specialists
- Contribute to product direction through rapid iteration and experimentation
- Operate with a product mindset, balancing speed, quality, and usability
- Make foundational decisions that shape long-term platform architecture
Required Skills & Experience
- 2–5 years of experience in backend or fullstack engineering in fast-paced environments
- Strong proficiency in Python
- Experience building production systems (APIs, backend services, data workflows, infrastructure tooling)
- Experience at VC-backed startups (Seed–Series B) OR 1–2 years at a high-caliber big tech company
- Strong communicator able to collaborate across engineering, operations, and customers
- Product-oriented mindset with ability to translate ambiguous requirements into shipped solutions
- Demonstrated ownership of projects end-to-end
- Undergraduate degree in Computer Science or related technical field
Nice to Have
- Experience working with reinforcement learning, machine learning, or model training pipelines
- Familiarity with agent frameworks or evaluation harnesses
- Exposure to data labeling systems, workflow tooling, or human-in-the-loop systems
- Experience working closely with customers to define technical requirements
- Experience at early-stage startups or in founder-like roles
- Comfort operating in fast-changing environments with evolving product requirements
What Does Not Work
- Frontend-leaning engineers without strong backend depth
- Candidates without hands-on experience building production systems
- Profiles focused primarily on research without shipping production software
- Candidates with multiple short tenures indicating limited ownership
- Big tech candidates without evidence of scrappiness or startup-style execution
- Lack of experience working with real-world workflows or operational systems
- Weak communication or inability to clearly explain technical tradeoffs
- Limited exposure to RL environments, agent systems, or infrastructure supporting model training
