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Handshake AI is building the fastest-growing AI data business, working directly with frontier AI labs to create evaluations and push the boundary of AI model development. The company has grown from $0 to ~$1B run rate and pays ~$60M monthly to over 30K individuals.
You'll join Handshake's India engineering team as a Software Engineer II focused on building the Reinforcement Learning Environments (RLE) platform—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 training and evaluation of the world's leading AI models.
In this role, you'll design, build, and scale the RLE platform and its infrastructure. You'll partner closely with US-based Engineering, Research, Product, and Operations teams to execute against a shared roadmap. Key responsibilities include designing and implementing scalable backend services and data generation pipelines, building modular environment domains that integrate with model training and evaluation workflows, improving platform reliability and observability, participating in technical design discussions, and contributing to architecture decisions. You'll write high-quality, maintainable code while helping improve engineering standards across the organization.
Success means the RLE platform becomes a trusted foundation for the next generation of AI model training, new environments launch quickly with high-quality infrastructure, systems remain reliable and observable, and you become a trusted engineering partner across distributed India and US teams.
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 ability to thrive in fast-moving, ambiguous environments
- Experience collaborating effectively with globally distributed engineering teams, including US-based teams
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 in fast-growing startups or high-growth engineering organizations
