Software Engineer, Infrastructure

About Normal Computing

Normal Computing builds silicon that turns thermal noise from an obstacle into a computational resource. Conventional chips spend most of their energy forcing determinism onto physics; ours compute with it. Stochastic in-memory asynchronous: the result is 10-100 more AI inference per dollar per watt.

We co-design the full stack: AI-native EDA systems in production with the worlds largest semiconductor companies and the advanced ASICs they make possible. Backed by $85M from the worlds leading deep-tech investors and built by scientists engineers and operators from the labs that built modern computing.

Normal works as one team across New York Silicon Valley London Copenhagen and Seoul. We hire people who want the hardest version of their craft across every discipline at every seniority.

The Role

As a Software Engineer at Normal you will build the backend runtimes and distributed systems behind our AI products. Youll design orchestration services execution environments internal APIs persistence layers and observability systems that allow AI agents to perform long-running work reliably.

These systems coordinate workloads across distributed environments execute code and tools securely preserve state across long-running sessions and recover cleanly from failures. Your work will turn ambitious AI prototypes into dependable products used in real customer workflows.

The role spans backend AI and platform engineering. Its focus is the application and runtime layer but not general-purpose cloud infrastructure or company-wide developer operations. Youll work closely with product AI research and platform engineers to define the interfaces between AI capabilities execution environments and production services.

On any given day you might design the execution model for a new AI capability build an orchestration service for autonomous workflows improve the scheduling and isolation of distributed workloads or create an API that makes a complex runtime capability easy for other engineers to use.

What Youll Own

• Runtime and Orchestration: Build the services that manage agent execution session lifecycles long-running workflows and distributed workloads.

• Backend Systems and APIs: Design reliable services data models and internal APIs used by product engineers AI engineers and execution systems.

• State and Failure Handling: Develop clear models for persistence retries queues leases cancellation recovery and other distributed-systems concerns.

• Execution Environments: Build software that schedules and manages containerized workloads in Kubernetes-backed environments including lifecycle isolation autoscaling and resource management.

• Reliability and Observability: Make evolving systems easier to operate through thoughtful metrics tracing debugging tools and well-defined failure modes.

• Developer Experience: Create abstractions and tools that allow other engineers to extend the platform without needing to understand every underlying implementation detail.

• Prototype-to-Production Engineering: Turn promising prototypes into durable systems by clarifying boundaries hardening critical paths and introducing operational patterns that scale.

• Technical Design: Lead design discussions around runtime architecture API boundaries state management execution models and operational tradeoffs.

What Makes You a Great Fit

• 4 years of software engineering experience in backend systems distributed systems developer platforms production infrastructure or a related area.

• Strong backend engineering fundamentals including API design data modeling concurrency debugging and testing.

• Experience designing and operating production services where reliability observability and maintainability matter.

• Experience reasoning about distributed state and failure modes including retries queues leases scheduling idempotency and long-running workflows.

• Practical experience with containers and Kubernetes-backed systems including workload lifecycle networking resource limits and production debugging.

• Experience with production data systems such as Postgres Redis or Valkey and object storage.

• Experience building orchestration systems workflow engines job schedulers sandboxes developer platforms or distributed execution systems.

• A track record of designing APIs and abstractions that other engineers can use confidently.

• Pragmatic judgment in fast-moving environments: you know when to improve an abstraction simplify it or ship the straightforward version.

• A strong sense of ownership for how your software behaves in production and how effectively others can use it.

Bonus Points

• Experience building systems for AI agents model orchestration code execution or other LLM-powered products.

• Deep Kubernetes knowledge such as controllers scheduling networking storage autoscaling or resource isolation.

• Experience with secure or sandboxed code execution.

• Background in reliability engineering infrastructure software or developer platforms at meaningful scale.

• Experience working in high-growth environments where systems and ownership boundaries are still taking shape.

Equal Employment Opportunity Statement

Normal Computing is an Equal Opportunity Employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. All qualified applicants will receive consideration for employment without regard to race color religion sex sexual orientation gender identity national origin disability veteran status or any other legally protected status.

Accessibility Accommodations

Normal Computing is committed to providing reasonable accommodations to individuals with disabilities. If you need assistance or an accommodation due to a disability please let us know at

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Required Experience:

IC