AI Product Engineer

Nscale is a GPU cloud engineered for AI, providing high-performance infrastructure for AI start-ups and large enterprises. The Principal Engineer (Product) role involves leading architecture decisions and hands-on delivery across platform capabilities, focusing on building scalable and reliable AI-native products.

Responsibilities:

• Design foundational platform capabilities across APIs, services, workflows, and data/control planes
• Implement reliable, secure systems that support Nscale’s managed AI services stack
• Drive architecture decisions that balance scalability, reliability, security, and cost efficiency across distributed systems
• Translate ambiguous product and platform challenges into crisp technical designs and execution plans
• Raise the engineering bar through rigorous design reviews and strong testing strategy
• Improve system resilience with robust observability and modern reliability practices
• Lead post-incident learning and continuous improvement across the platform
• Apply strong code quality, performance, and production engineering fundamentals in day-to-day delivery
• Embed security, IAM, privacy, and governance into system design and delivery by default
• Strengthen operational readiness across services and platform components
• Support production excellence through incident response and ongoing system improvement
• Contribute to high-availability service design with attention to reliability and cost optimisation
• Partner with squads across the firm to align on interfaces, ownership, and execution
• Communicate technical direction clearly across engineers, PMs, and executives
• Balance short- and long-term priorities to keep teams moving while building for scale
• Scale team effectiveness through alignment, strong design, and clear technical communication
• Improve delivery velocity through platform leverage, automation, and tooling
• Use AI responsibly to accelerate software delivery and scale operations
• Leverage modern cloud-native patterns and systems thinking to evolve large-scale platforms
• Advance the managed AI services stack with practical, high-impact engineering improvements

Requirements:

• 15+ years building and shipping production platforms at scale
• Strong experience with distributed systems and cloud-native environments
• Proven expertise with Kubernetes, CI/CD, and reliability patterns
• Proficiency in Python, Go, and/or Rust
• Strong fundamentals in code quality, testing, and performance
• Deep experience in observability, incident response, and continuous improvement
• Strong security fundamentals including IAM, data protection, and governance in production environments
• Experience collaborating effectively across engineers, PMs, and executives
• Ability to leverage AI to build, evolve, and maintain large-scale systems
• Experience with developer platforms, control planes, APIs, SDKs, or CLIs is a plus