Software Engineer, Agent Infrastructure

Where multiple locations are listed for this role, the position may be based in any of those locations, with priority determined according to the order of listing.At Simular, we’re building the next generation of computer user agents - AI systems that can actually use your computer for you. Our backend powers everything from live VM orchestration to agent planning and execution.We’re looking for a generalist backend/infrastructure engineer who thrives in ambiguity, has strong architectural instincts, and wants to own big, evolving pieces of our system. This isn’t a narrow “DevOps” or “API engineer” role - you’ll be shaping how our platform scales and evolves over the next few years.What you’ll doDesign and scale the systems behind Simular Cloud and our cross-platform agents.Own critical backend services: APIs, data flows, billing, observability, deployment pipelines.Tackle hard infra challenges: VM orchestration, reproducibility, parallel execution, reliability.Spot when it’s time to split/refactor services and lead that evolution.Explore new directions as the product grows - from microVMs to multi-agent orchestration, fine-tuned model endpoints, or community task galleries.Collaborate with product and research to turn ideas into production systems.You might be a fit ifYou’re a strong programmer with solid fundamentals (Python, Go, Rust, or similar).You have experience with some of: cloud infra, distributed systems, virtualization, CI/CD - but more importantly, you can pick up whatever’s needed.You think in terms of architecture, not just code: you know when to hack and when to design for the long run.You’re comfortable owning big ambiguous problems end-to-end.Bonus: you’ve touched GPU scheduling, large-scale ML infra, or scaling SaaS systems.

• You’re a strong programmer with solid fundamentals (Python, Go, Rust, or similar).
• You have experience with some of: cloud infra, distributed systems, virtualization, CI/CD - but more importantly, you can pick up whatever’s needed.
• You think in terms of architecture, not just code: you know when to hack and when to design for the long run.
• You’re comfortable owning big ambiguous problems end-to-end.
• Bonus: you’ve touched GPU scheduling, large-scale ML infra, or scaling SaaS systems.