Senior Engineering Manager, Reinforcement Learning Environments (RLE)

Edtech.com's Summary

Handshake is hiring a Senior Engineering Manager, Reinforcement Learning Environments (RLE). The role leads the RLE team to build sandbox environments where AI models learn complex workflows across domains like software engineering, finance, and legal research. The position involves shaping technical direction, managing a team of engineers, and collaborating with research and product teams to deliver scalable, reliable environments for reinforcement learning.

Highlights

Lead and grow a team of 8-9 engineers building reinforcement learning environments
Manage senior engineers and develop future engineering leaders
Partner with research, product, and operations teams to define roadmap and priorities
Drive scalable, reliable, and extensible technical architecture for environment systems
Build plug-and-play environments integrated with model training pipelines
Establish best practices for reliability, observability, and performance
Require 3+ years engineering management and 5+ years hands-on engineering experience
Strong background in platform systems, distributed systems, or infrastructure
Experience with internal platforms, data pipelines, and research tools preferred
Willingness to work onsite in San Francisco 5 days per week

Senior Engineering Manager, Reinforcement Learning Environments (RLE) Full Description

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 worldâs 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

Weâre 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 â 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 â not just prediction, but task completion, quality, and robustness in complex workflows.

As a Senior Engineering Manager, youâll shape the technical direction and long-term strategy of this critical platform. Youâll 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 8â9 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 supportedâand thrive at work and in life.

The below benefits are for full-time US employees.

ð¯ Ownership: Equity in a fast-growing company

ð° Financial Wellness: 401(k) match, competitive compensation, financial coaching

ð¼ Family Support: Paid parental leave, fertility benefits, parental coaching

ð Wellbeing: Medical, dental, and vision, mental health support, $500 wellness stipend

ð Growth: $2,000 learning stipend, ongoing development

ð» Remote & Office: Internet, commuting, and free lunch/gym in our SF office

ð Time Off: Flexible PTO, 15 holidays + 2 flex days

ð¤ Connection: Team outings & referral bonuses

Explore our mission, values, and comprehensive US benefits at joinhandshake.com/careers.

Original Job Description