AI Product Engineer

About Nscale

Nscale is the GPU cloud engineered for AI. We provide cost-effective, high-performance infrastructure for AI start-ups and large enterprise customers. Nscale enables AI-focused companies to achieve superior results by reducing the complexity of AI development. Our GPU cloud bolsters technical capabilities and directly supports strategic business outcomes, including cost management, rapid innovation, and environmental responsibility.

We thrive on a culture of relentless innovation, ownership, and accountability, where every team member takes pride in their work and drives it with excellence and urgency. As an Nscaler, you’ll build trust through openness and transparency, where everyone is inspired to do their best work. If you join our team, you’ll be contributing to building the technology that powers the future.

About the Role

We’re hiring a Principal Engineer (Product) to build and evolve Nscale’s vertically integrated managed AI services stack.

In this role, you’ll lead critical architecture decisions while staying hands-on in delivery across foundational platform capabilities including APIs, services, workflows, and data/control planes . You’ll work closely with squads across the business, partnering with engineers, product managers, and executives to align interfaces, ownership, and operational readiness.

This is a high-impact opportunity for an experienced engineer who thrives in ambiguity, turns complex problems into clear designs, and raises the bar on quality, security, and operational excellence. Your work will directly shape how Nscale ships reliable, secure, and scalable AI-native products with real enterprise impact.

What you'll be doing

Platform Architecture & Delivery

• 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

Engineering Quality & Reliability

• 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

Security, Governance & Operational Excellence

• 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

Cross-Functional Technical Leadership

• 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

Platform Leverage & AI-Accelerated Execution

• 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

KPIs

• Scalability, reliability, security, and cost efficiency of distributed systems
• Delivery velocity through platform leverage, automation, and tooling
• Operational excellence across observability, incident response, and post-incident learning
• Cross-squad alignment on interfaces, ownership, and operational readiness<