About the Company

A fast-growing, post-Series A startup is building the data and evaluation infrastructure used by leading AI labs to improve next-generation models. The team works closely with top-tier organizations to create high-quality datasets and advanced evaluation systems that go beyond traditional benchmarks. It’s a small, high-impact environment where engineers directly influence how cutting-edge AI systems are trained and validated.

About the Role

This is a highly hands-on engineering role with end-to-end ownership across both research and platform initiatives. You’ll work on designing RL environments, agentic systems, and evaluation frameworks, while also building scalable infrastructure, human-in-the-loop platforms, and data pipelines.

The scope is intentionally broad—ranging from prototyping research-driven systems to deploying distributed workloads and improving production reliability. You’ll collaborate closely with research, product, and design teams to ship quickly without compromising quality.

Key Responsibilities

• Build and scale systems such as RL environments, APIs, and data/evaluation platforms
• Develop human-in-the-loop workflows and annotator tooling
• Contribute to distributed infrastructure and data pipelines
• Write clean, maintainable code and participate in code reviews
• Solve complex scalability and reliability challenges
• Support core systems used by leading AI labs

Requirements

Technical

• Strong programming skills in Node.js/TypeScript, Python, or Go
• Solid understanding of distributed systems, scalability, and system design
• Experience with cloud platforms (AWS or GCP), Kubernetes, APIs, and NoSQL databases
• Ability to balance speed vs. reliability and make sound engineering trade-offs
• Active GitHub with meaningful, production-level or personal projects

Execution & Ownership

• High ownership mindset with the ability to work autonomously
• Proactive problem-solver who drives solutions end-to-end
• Comfortable operating in fast-paced, high-intensity environments
• Focus on delivering simple solutions to complex problems

Communication

• Strong written and verbal communication skills
• Clear motivation to work in a startup environment focused on AI

Nice to Have

• Experience with RL systems, agentic workflows, or human-in-the-loop platforms
• Background in high-performance environments (e.g., quant firms or fast-scaling startups)
• Previous founding experience or early-stage startup exposure

Ideal Profile

• Strong builder mentality with a portfolio of real, hands-on projects
• Thrives in challenging, fast-moving environments
• Operates with a high level of ownership and accountability
• Motivated to work at the forefront of AI development