We are actively growing, so if you are an exceptional candidate excited to work on the cutting edge of physical AI and don’t see a role that exactly fits you below you can contact us directly with your resume via jobsarchetypeaiio.

About The Role We’re looking for a highly motivated backend engineer with a passion for building performant, scalable, and resilient distributed systems. You’ll work closely with researchers, ML engineers, and product teams to bring cutting-edge AI capabilities into production—at scale, with reliability, and under real-world constraints.

This is an opportunity to own critical services, optimize for latency and throughput, and contribute to some of the most advanced systems in production today.

Core Responsibilities

• Architect, implement, and maintain distributed systems that support high-throughput, low-latency AI model inference and data services.
• Partner with ML researchers and product teams to turn experimental models into production-grade services.
• Continuously optimize performance across GPU clusters, cloud infrastructure, and backend systems.
• Build tooling and observability to monitor system health, identify bottlenecks, and proactively resolve instability.
• Introduce new techniques, architectures, and best practices to push the limits of scalability, efficiency, and reliability.
• Own problems end-to-end—from design to deployment—with a strong bias toward quality, automation, and continuous improvement.
• Balance rapid iteration on early-stage systems with long-term maintainability and architectural soundness.
• Contribute to a culture of engineering excellence, mentorship, and team-first collaboration.

Minimum Qualifications

• 7+ years of professional software engineering experience, with a focus on backend or distributed systems.
• Deep understanding of distributed systems fundamentals—concurrency, consistency, replication, fault tolerance, networking.
• Experience building and operating production-grade systems at scale in cloud environments (e.g., Azure, AWS, GCP).
• Strong debugging, instrumentation, and observability skills across distributed systems.
• Demonstrated ownership of complex technical problems and ability to learn and adapt quickly.

Preferred Qualifications

• Proven track record of scaling systems through rapid growth and rebuilding or refactoring for new demands.
• Proficiency in systems programming languages (e.g., Rust, C++) and scripting environments (e.g., Python).
• Experience designing internal tools or platforms to support developer productivity and experimentation.
• Strong product intuition, and ability to collaborate closely with cross-functional teams including research and design.
• Familiarity with modern ML stacks and hardware acceleration (e.g., PyTorch, CUDA).

What We Value

• Ownership – You take initiative, follow through, and care deeply about quality and outcomes.
• Motivation – You’re driven to solve complex problems and continuously raise the bar for yourself and your team.
• Excellence – You bring discipline, clarity, and rigor to your craft—and help others do the same.
• Collaboration – You work well with others, mentor generously, and contribute to a high-trust, high-performance culture.