Senior Engineering Manager, Reinforcement Learning Environments (RLE) at Handshake

ABOUT HANDSHAKE Handshake is the career network for the AI economy. 20 million knowledge workers, 1,600 educational institutions, 1 million employers (including 100% of the Fortune 50), and every foundational AI lab trust Handshake to power career discovery, hiring, and upskilling, from freelance AI training gigs to first internships to full-time careers and beyond. This unique value is leading to unparalleled growth; in 2025, we tripled our ARR at scale. Why join Handshake now: - Shape how every career evolves in the AI economy, at global scale, with impact your friends, family and peers can see and feel - Work hand-in-hand with world-class AI labs, Fortune 500 partners and the world’s top educational institutions - Join a team with leadership from Scale AI, Meta, xAI, Notion, Coinbase, and Palantir, among others - Build a massive, fast-growing business with billions in revenue About the Role We’re expanding our team and seeking a Senior Engineering Manager to lead our Reinforcement Learning Environments (RLE) team. The RLE team builds the sandbox environments where frontier AI models learn complete, end-to-end workflows. These environments simulate real-world professional domains such as software engineering, finance, and legal research — complete with realistic tools, constraints, and feedback loops. Instead of learning from static examples, models practice doing the work: navigating multi-step tasks, using domain-specific tools, handling ambiguity, and optimizing for real outcomes. Researchers use these environments and the data they generate to train state-of-the-art models with reinforcement learning grounded in execution — not just prediction, but task completion, quality, and robustness in complex workflows. As a Senior Engineering Manager, you’ll shape the technical direction and long-term strategy of this critical platform. You’ll lead a growing team (currently 9 engineers) and will likely manage an Engineering Manager in the near term. This is a highly strategic role sitting at the intersection of platform engineering, applied AI infrastructure, research tooling, and human-in-the-loop operations systems. Location: San Francisco, CA| 5 days/week in-office - Lead and grow a high-performing team of 8–9 engineers building reinforcement learning environments - Manage, mentor, and develop senior engineers and future engineering leaders - Partner closely with research, product, and operations teams to define roadmap and execution priorities - Drive technical architecture for scalable, reliable, and extensible environment systems - Build plug-and-play environments that integrate seamlessly with model training pipelines - Balance platform rigor with operational complexity and data quality requirements - Establish engineering best practices around reliability, observability, and performance - Foster a culture of ownership, velocity, and high technical standards Desired Capabilities - 3+ years of engineering management experience, with increasing scope and ownership - Experience managing senior engineers; experience managing an Engineering Manager (or equivalent scope) strongly preferred - 5+ years of prior hands-on engineering experience - Strong technical background in platform systems, distributed systems, or full-stack infrastructure - Experience building internal platforms, data pipelines, or research-facing tools - Proven ability to operate effectively in fast-paced, ambiguous environments - Experience driving cross-functional alignment across engineering, research, and operations - Willingness to work in-office in San Francisco 5 days/week Extra Credit - Experience in reinforcement learning, simulation systems, or AI training infrastructure - Background in human-in-the-loop systems, data annotation platforms, or workflow tooling - Experience in operations-heavy, tech-enabled organizations - Familiarity with cloud infrastructure (AWS or GCP), APIs, and modern web stacks (e.g., React, TypeScript, Node.js, Python) - Experience building systems used by AI researchers or applied ML teams What Success Looks Like - RLE becomes the default platform researchers use to train reinforcement learning workflows - New domains (e.g., finance, legal, SWE) can be launched quickly and reliably - Environment reliability and data quality are trusted by top AI research partners - The team scales with strong technical leaders who can independently drive new verticals - The RLE platform materially accelerates model capability in real-world task completion Perks Handshake delivers benefits that help you feel supported—and thrive at work and in life. The below benefits are for full-time US employees. 🎯 Ownership: Equity in a fast-growing company 💰 Financial Wellness: 401(k) match, competitive compensation, financial coaching 🍼 Family Support: Paid parental leave, fertility benefits, parental coaching 💝 Wellbeing: Medical, dental, and vision, mental health support, $500 wellness stipend 📚 Growth: $2,000 learning stipend, ongoing development 💻 Remote & Office: Internet, commuting, and free lunch/gym in our SF office 🏝 Time Off: Flexible PTO, 15 holidays + 2 flex days 🤝 Connection: Team outings & referral bonuses Explore our mission, values, and comprehensive US benefits at joinhandshake.com/careers [Upgrade to PRO to see link]