AI Product Engineer

Nscale•Seattle, WA

3d•$225,000 - $250,000•Hybrid

About The Position

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.

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

Nice To Haves

Experience with developer platforms, control planes, APIs, SDKs, or CLIs is a plus

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