Engineering Manager, RLE

About Handshake
Handshake was founded on a simple belief that everyone deserves a path to a great career, regardless of where they went to school or who they know. Today, we power 25 million job seekers, 1 million+ employers, and 1,600 educational institutions.

In 2025, we started Handshake AI and built the fastest-growing AI data business in history. We work directly with frontier AI lab researchers to create evaluations, publish benchmarks, and push the boundary of data. We’ve grown from $0 to ~$1B run rate and pay ~$60M to over 30K individuals every month.

 
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

Partner hand-in-hand with world-class AI labs, Fortune 500 partners and the world’s top educational institutions

Work together with engineers, scientists, operators, and more from Palantir, Meta, Scale AI, and former YC founders

Build a massive, fast-growing business with billions in revenue

About Handshake AI
Human data is the core infrastructure to AI advancement. Frontier AI labs currently improve model capabilities with various data-intensive post-training techniques. We believe that data spend for AI training will increase by 3-5x in the next few years and continue for much longer as models take on new domains. Handshake AI supports all of the frontier AI labs, working on their most complex data at the largest scale.

We are building our India team to help accelerate the development of frontier models. This team is a critical, strategic investment for us - we have grown the team 3x in the past six months to help fuel our next phase of growth. India-based teammates will work hand-in-hand with US-based teams to scope, execute, and deliver critical human data projects to Frontier Labs and other customers.

About the Role
We’re hiring a Senior Software Engineer to build our Reinforcement Learning Environments (RLE) platform—the interactive systems where frontier AI models learn to complete real-world work.

RLE environments simulate workflows (e.g., software engineering, finance, legal) with realistic tools, constraints, and feedback loops. The data generated powers training and evaluation for model quality, robustness, and task completion.

This is a high-ownership role with direct impact on how models learn and how quickly new domains scale.

 
What You’ll Do

Build and scale our reinforcement learning environments and the platforms behind them

Drive architecture for scalable, reliable, extensible environment systems and data generation pipelines

Partner with Research, Product, and Ops to turn ambiguous needs into production systems

Build modular, plug-and-play domains that integrate cleanly with training and evaluation loops

Raise the bar on reliability, observability, performance, and data quality

What We’re Looking For

7+ years building backend, distributed systems, or ML infrastructure

Proficiency with Node.js And ReactJS OR TypeScript, with deep knowledge of backend architectures.

Strong command of relational databases (e.g., PostgreSQL), data modeling, system design, and distributed systems principles.

Experience with cloud infrastructure (AWS, GCP), CI/CD pipelines, and operating production systems at scale.

Strong applied AI experience is required

Full-stack or backend-leaning engineers preferred.

Nice to Have

Experience with RL training infrastructure, simulation systems, or evaluation platforms

Working in an operations-heavy, tech-enabled environment

Experience supporting applied ML or AI research teams

What Success Looks Like

RLE becomes a trusted platform for training workflow-capable models

New domains launch quickly with high-quality data

Systems are reliable, scalable, and drive measurable model improvements

You’ll Thrive Here If You:

Are motivated by solving operational problems that have direct, measurable impact.

Want to be part of a company shaping the future of…