Software Engineer II, Reinforcement Learning Environments

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 Software Engineer II to help build our Reinforcement Learning Environments (RLE) platform—the interactive systems where frontier AI models learn to complete real-world work. RLE environments simulate end-to-end workflows across domains like software engineering, finance, legal research, and business operations with realistic tools, constraints, and feedback loops. The interaction data generated powers the training and evaluation of the world's leading AI models. As part of our growing engineering organization in India, you'll partner closely with Engineering, Research, Product, and Operations teams in the US to build the platforms powering the next generation of AI. You'll own meaningful technical projects, contribute to platform architecture, and help build reliable systems that enable researchers to rapidly develop and evaluate frontier AI models. Location: Bengaluru, India. This is an in-office role. WHAT YOU'LL DO - Design, build, and scale our Reinforcement Learning Environments (RLE) platform and the infrastructure that powers it - Partner closely with Engineering, Research, Product, and Operations teams in the US to execute against a shared roadmap - Design and implement scalable backend services and data generation pipelines - Build modular environment domains that integrate seamlessly with model training and evaluation workflows - Improve platform reliability, observability, performance, and developer productivity - Participate in technical design discussions and contribute to architecture decisions - Write high-quality, maintainable code while helping improve engineering standards and best practices WHAT WE'RE LOOKING FOR - 3+ years of professional software engineering experience building backend systems, distributed systems, or platform infrastructure - Strong proficiency with TypeScript, React, and modern backend architectures - Strong understanding of PostgreSQL, data modeling, distributed systems, and system design - Experience building and operating production systems on AWS or GCP - Strong problem-solving skills and the ability to thrive in fast-moving, ambiguous environments - Experience collaborating effectively with globally distributed engineering teams, including teams based in the US NICE TO HAVE - Experience with reinforcement learning infrastructure, simulation systems, or AI evaluation platforms - Experience building internal developer platforms or workflow orchestration systems - Familiarity with Docker, Kubernetes, and CI/CD pipelines - Experience supporting applied ML or AI research teams - Experience working in a fast-growing startup or high-growth engineering organization WHAT SUCCESS LOOKS LIKE - Reinforcement Learning Environments become a trusted platform powering the next generation of AI model training - New environments launch quickly with high-quality, scalable infrastructure - Systems are reliable, observable, and built to support rapid iteration - You become a trusted engineering partner across the India and US teams, helping deliver critic