AI Platform Engineer, Backend

About the role

Own it end-to-end: architecture, implementation, deployment, and long-term maintenance.
Build for real environments, design modular, reusable APIs (REST, gRPC, event-driven) and backend architectures that meet enterprise and government uptime expectations.
Think in first principles, break down complex, open-ended problems into clear technical designs and ship production-ready systems with speed and rigor.
Optimize continuously, improve latency, throughput, and cost efficiency through profiling, thoughtful system design, and iteration.
Partner closely with Product, ML, Infrastructure, and customer-facing teams, building systems that are intuitive, reliable, and developer-friendly.

Responsibilities

• Own it end-to-end: architecture, implementation, deployment, and long-term maintenance.
• Build for real environments, design modular, reusable APIs (REST, gRPC, event-driven) and backend architectures that meet enterprise and government uptime expectations.
• Think in first principles, break down complex, open-ended problems into clear technical designs and ship production-ready systems with speed and rigor.
• Optimize continuously, improve latency, throughput, and cost efficiency through profiling, thoughtful system design, and iteration.
• Partner closely with Product, ML, Infrastructure, and customer-facing teams, building systems that are intuitive, reliable, and developer-friendly.

Requirements

• 3+ years building production systems with strong fundamentals in distributed systems (consistency, availability, failure modes, retries, idempotency) and deep proficiency in Go, TypeScript, Rust, Python, or similar.
• Proven ability to design from first principles, with experience building shared infrastructure, internal platforms, or developer-facing services and strong intuition for DX and long-term maintainability.
• Experience owning services with real uptime responsibility, plus familiarity with observability tooling (metrics, logging, tracing) and incident response.
• Track record designing, operating, and evolving APIs and services at scale.

Qualifications

• Experience with AI/ML platforms, inference systems, or data-intensive pipelines.
• Familiarity with Kubernetes and cloud-native service deployment.
• Exposure to multi-tenant, regulated, or government environments.
• Experience with real-time or streaming data systems.

Skills

• Strong fundamentals in distributed systems (consistency, availability, failure modes, retries, idempotency).
• Deep proficiency in Go, TypeScript, Rust, Python, or similar programming languages.
• Experience building shared infrastructure, internal platforms, or developer-facing services.
• Ability to design from first principles and break down complex problems into clear technical designs.
• Experience with observability tooling (metrics, logging, tracing) and incident response.
• Experience owning services with real uptime responsibility.
• Experience with AI/ML platforms, inference systems, or data-intensive pipelines.
• Familiarity with Kubernetes and cloud-native service deployment.
• Exposure to multi-tenant, regulated, or government environments.
• Experience with real-time or streaming data systems.

Benefits

• Competitive salary plus equity.
• Daily lunches.
• Commuter benefits.
• 401(k).
• Medical, Dental, and Vision coverage.
• Unlimited PTO.

Pay

Competitive salary plus equity.

Schedule

Full-time.