Software Engineer II, Reinforcement Learning Environments

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.

Responsibilities

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

Requirements

6+ 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

Benefits

Generous Equity Grant vested over 4 years; Housing Bonus: 1.3 Lakhs spread throughout the first year; Well Defined Performance Bonus ranging between 10 - 100% of base; Medical Insurance Coverage; Food credit for every in person day