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.