Software Engineer

• Build the training loop, not a wrapper. Our engineers work at the core of the RL pipeline - building the systems that generate training signal for frontier AI agents, not dashboards on top of someone else’s model.
• Real customers, real usage. We already ship software that leading AI teams depend on daily.
• Massive scope and ownership. On a ~10-person team you’ll touch backend systems, data pipelines, automation infrastructure, internal tools, and customer-facing prototypes - with the autonomy to drive projects end to end.
• Founder-led technical culture. Work directly alongside researchers and infrastructure engineers in a tight feedback loop, with no layers between you and the problem., We’re looking for a backend-leaning software engineer with experience on AI-related projects who can scale and automate our post-training pipeline. You’ll thrive in a fast-moving, research-adjacent environment and bring a track record of optimizing systems for scale, driving down cost, and iterating quickly on Python-based stacks. This is a hands-on, individual-contributor role., * Build and optimize automation pipelines that streamline the post-training stack for scale and cost efficiency
• Maintain and support high-concurrency infrastructure powering customer training pipelines
• Work with researchers and founders to turn experimental workflows into robust, production-ready systems
• Develop backend services and APIs for environment generation, trace ingestion, and telemetry
• Collaborate on parallelization and coordination of multiple agents across distributed systems
• Ship pragmatic, high-quality software in a flat, deeply technical team

Tech stack: Python, Rust, FastAPI, TypeScript, Agent SDKs, Redis, distributed systems, CPU-based infrastructure

Do you have experience in Scalable systems?, Required

• 0-8 years of experience in software engineering, backend, or AI-adjacent work
• Currently working on AI/agent-related projects
• Strong Python proficiency for rapid iteration
• Experience scaling systems at startups or big tech
• Built backend systems, data pipelines, or automation infrastructure
• Comfortable navigating and iterating quickly in large Python codebases
• Experience with high-concurrency backend infrastructure (FastAPI, queuing, Redis)

Preferred

• Computer Science degree
• Experience with agent SDKs, LLM tooling, or RL pipelines, * Intro Chat (30 min) with a founding team member - background, motivations, fit, and logistics.
• Technical Interview (30-60 min) - a collaborative, experimental-design problem-solving session (not a traditional coding test).
• On-site Work Trial (1-3 days) - working alongside the team on real or representative tasks.

We’re an early-stage, venture-backed applied research lab building the foundational infrastructure to train specialized AI agents. We turn real-world data streams into high-fidelity simulated environments that generate the training signal needed to make capable models - supporting frontier AI labs, hyperscalers, and enterprises building AI systems for complex, high-stakes work. Compute and algorithms are commoditizing fast; reinforcement-learning data remains the bottleneck, and we’re built to scale training environments automatically from proprietary real-world data.

Founded 2025 · Small, fully technical team (~10) · Currently raising Series A · San Francisco.