Senior AI Product Engineer

Location: Houston, New York, San Francisco, or Seattle, United States

Salary: $180,000–$260,000 USD per year, plus potential bonus, equity, and/or commission programs.

Company

Nscale builds a vertically integrated generative AI cloud platform spanning data centers, software, and AI applications.

What you will do

• Lead technical design and end-to-end delivery for major product subsystems and complex features.
• Own architectural decisions across API contracts, deployment strategy, and cloud service design.
• Set standards for test coverage, observability, reliability, incident response, and service stability.
• Mentor engineers through design reviews, code reviews, and pairing.
• Collaborate with AI platform, infrastructure, and product teams.
• Identify technical debt and scalability constraints, contribute to hiring, and create design documentation.

Requirements

• 5–8 years of software engineering experience.
• Deep backend or full-stack development experience at scale with Python, TypeScript, Go, or similar technologies.
• Experience designing and operating API platforms or developer-facing cloud services.
• Experience with Kubernetes, distributed systems, observability stacks, control plane and data plane separation, and scalable fault-isolation patterns.
• Production ownership including on-call rotations, incident response, SLOs, error budgets, alerting, reliability monitoring, and live-system debugging.
• Experience with declarative provisioning, versioned configuration contracts, long-running workflows, usage metering, cost attribution, and clear technical communication.

Nice to have

• Experience building or consuming SDKs, Terraform providers, or cloud-platform extensibility layers.
• Familiarity with Terraform, Pulumi, and infrastructure-as-code practices.
• Experience building AI-integrated features such as LLM inference APIs, fine-tuning interfaces, or agentic workflows.
• Experience modelling deployable units with typed inputs, readiness checks, defaults, and published outputs.
• Working knowledge of AI/ML infrastructure, model serving, evaluation, and lifecycle management.

Culture & Benefits

• Culture centered on innovation, ownership, accountability, openness, and transparency.
• Collaborative, adaptable, and resilient working environment.
• Potential medical, dental, and vision coverage.
• Flexible paid time off and parental leave.
• Retirement plan participation and possible bonus, equity, and/or commission programs.