Founding Member of Technical Staff ($200K + Equity) AI Agents × Financial Services

This role is being recruited by CoffeeSpace on behalf of a YC-backed AI startup building reinforcement learning environments for frontier AI agents. We’re identifying a small number of exceptional platform engineers from our network. If there’s a strong fit, we’ll introduce you directly to the founding team. Compensation: $200k base + 0.25%–0.5% equity Employment type: Full-time About the company This company builds realistic reinforcement learning environments that help frontier AI labs train and evaluate agents on complex, long-horizon financial workflows. Their work sits at the intersection of AI agents, financial services, infrastructure, and synthetic data. They create environments where models can practice tasks like financial analysis, spreadsheet modeling, quantitative workflows, document generation, and other verifiable business processes. The company recently raised a $6M seed round, is backed by YC, and is already working with major frontier model companies as paying customers. Revenue has grown quickly, moving from hundreds of thousands in 2025 to nearly $10M closed this year, with a path toward mid-eight figures by year-end. The team is small, technical, and moving fast. This is an early engineering role with meaningful ownership over both the product and the engineering culture. About the role You’ll join as a Founding Member of Technical Staff focused on building the infrastructure behind the company’s RL environments. This is a backend/platform-heavy role, but it is not isolated infrastructure work. You’ll work close to customers, researchers, subject matter experts, and the founding team to build systems that make RL environment creation faster, more scalable, and more realistic. You’ll help build the platform that supports training, inference, evaluation, analytics, synthetic data pipelines, and domain-specific reward/verifier systems. What you’ll do Build RL environment training and inference infrastructure that can support customer usage at scale Develop internal platforms that make RL environment creation 10x to 100x faster and higher quality Design systems for increasingly realistic, long-horizon AI agent environments Build synthetic data pipelines for realistic financial and business tasks Create analytics to track environment costs, bottlenecks, SME workflows, and platform performance Craft domain-specific verifiers and reward functions for financial services and adjacent workflows Work directly with users, customers, and subject matter experts to understand what needs to be built Help establish engineering culture and practices from the ground up The ideal candidate 2 to 6 years of experience in backend, platform, or infrastructure engineering Experience at a pre-seed, seed, or Series A startup, or experience as a former founder Strong Python and/or TypeScript ability Comfortable with Docker, cloud infrastructure, and modern AI coding tools Experience or strong interest in ML tooling, agent platforms, evals, benchmarks, QA tooling, or RL environments High ownership, fast iteration speed, and comfort operating with ambiguity Product-minded engineer who can prioritize across a large roadmap Comfortable talking directly with customers, users, or subject matter experts Based in the Bay Area or highly motivated to relocate quickly to San Francisco Nice to have Experience building evaluations, benchmarks, or RL environments for AI agents Experience with financial services, fintech, quantitative workflows, or financial modeling Experience designing reward functions, verifiers, or synthetic data systems CS, ML, or related technical degree Founder or early-stage startup background This role is probably not for you if You want pure research without product or customer ownership You prefer large-company structure, clearly scoped tickets, and slower release cycles You have only worked in big tech and do not want the pace of an early-stage startup You are looking for a mostly remote role You are a pure MLE or researcher and do not want to build platform/infrastructure systems Why this role is remarkable You’ll work on one of the most important bottlenecks in frontier AI: giving agents realistic environments where they can learn, fail, improve, and be evaluated on economically meaningful tasks. You’ll be joining early, with strong compensation, meaningful equity, and direct exposure to major AI labs and financial services use cases. This is a rare chance to build infrastructure that sits underneath the next generation of AI agents, while helping shape the engineering culture of a fast-growing seed-stage company. Benefits include fully covered healthcare, relocation support, 401k matching, meals, gym support, and transportation support. Next steps Apply via this LinkedIn job post We’ll review and reach out if there’s a strong match If aligned, we’ll introduce you directly to the founding team If this role isn’t the right fit, we may suggest and make introductions to other high-signal startup roles we’re recruiting for, always with your permission This is a real, active role that CoffeeSpace is recruiting for in close partnership with the hiring team. We don’t post speculative roles and work directly with teams on their actual hiring needs. #J-18808-Ljbffr CoffeeSpace