Platform Engineer - Reinforcement Learning Infrastructure for Financial Services AI

This role is being recruited by CoffeeSpace on behalf of an anonymous venture-backed AI startup building reinforcement learning environments and infrastructure for frontier AI systems in financial services.

We’re identifying a small number of exceptional platform and full-stack engineers from our network. If there’s a strong fit, we’ll introduce you directly to the founding team.

Location: San Francisco, CA

Compensation: $200K–$250K base + 0.15%–0.3% equity

Employment type: Full-time

Work setup: 5 days in-office

Visa: Open to visa transfers, including OPT and H-1B transfers

About the company

This company builds reinforcement learning environments and benchmarks used to train and evaluate advanced AI agents for financial services workflows.

They work with frontier AI labs and financial institutions on domains like investment banking, private equity, hedge funds, Excel modeling, and other complex computer-based tasks.

The company has raised $8.5M, is still a small early-stage team, and is scaling quickly as demand for high-quality RL environments grows.

About the role

As a Platform Engineer, you’ll help build the infrastructure, tooling, and environments used to train and evaluate frontier AI agents.

You’ll work across platform engineering, ML infrastructure, synthetic data, evaluation systems, and product development, with meaningful ownership from day one.

What You’ll Do

• Build scalable training and inference infrastructure for RL environments
• Develop realistic, long-horizon environments for frontier AI agents
• Build software that increases the quality and throughput of environment creation
• Design synthetic data pipelines and domain-specific verifiers
• Create internal platforms and analytics for managing costs, workflows, and bottlenecks
• Work directly with engineers, customers, and subject-matter experts

Outcomes

• Scale infrastructure supporting production RL environments
• Make environment creation dramatically faster and more reliable

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• Improve the realism and difficulty of agent benchmarks
• Build robust verifier and reward systems for financial workflows
• Establish strong engineering systems as the company grows
• Help the team deliver high-quality environments to major AI labs and financial institutions

Why This Role Is Compelling

• Work directly on frontier AI training and evaluation infrastructure
• Build RL environments used for complex real-world financial workflows
• Join a small team with significant ownership and early-stage equity
• Work with major AI labs and financial institutions
• Operate across platform engineering, AI infrastructure, and product
• Receive strong benefits including healthcare, relocation support, meals, transportation, and 401(k) matching

The Ideal Candidate

• 3–8 years of platform, backend, or full-stack engineering experience
• Experience at an early-stage startup or as a former founder
• Strong Python, TypeScript, infrastructure, and systems engineering fundamentals
• Experience building ML tooling, AI agent platforms, evaluations, benchmarks, or RL environments
• Comfortable shipping quickly and owning projects end-to-end
• Strong interest in AI, with financial services experience a plus

Next steps

1. Apply via this LinkedIn job post
2. We’ll review and reach out if there’s a strong match
3. If aligned, we’ll introduce you directly to the founding team
4. 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.

A quick note on authenticity

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.