Software Engineer

About the Company 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. Why Join 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. The Role 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. What You'll Do 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 Qualifications 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 Details Compensation: $180,000–$280,000 + competitive equity Location: San Francisco, CA — on-site (relocation support available for the right candidate) Employment type: Full-time Visa sponsorship: Not available Interview Process 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. Offer. #J-18808-Ljbffr