---
title: 'Software Engineer, Agent Systems at Normal Computing Corporation'
canonical: 'https://feeny.ai/job/software-engineer-agent-systems-normal-computing-corporation-new-york-9mc74m2d7yp9'
type: 'job'
last_seen: '2026-09-10'
---

# Software Engineer, Agent Systems at Normal Computing Corporation

- **Company:** Normal Computing Corporation
- **Location:** New York, NY
- **Employment:** full-time
- **Work type:** hybrid
- **Posted:** 2026-08-10
- **Last confirmed live:** 2026-09-10
- **Apply:** https://jobs.ashbyhq.com/normalcomputing/51c718cf-7187-472b-b126-86b1b2bb9896

## Job description

Normal Computing | Build with Us Normal is an applied AI company solving the hardest problems in AI and silicon. We build foundational hardware and software for the semiconductor industry, critical AI infrastructure, and the broader systems that power our world, in partnership with the world's most advanced institutions. We work as one team across New York City, Silicon Valley (Mountain View), London, Copenhagen, and Seoul.

## The Role

As a Software Engineer at Normal, you will build the backend runtimes and distributed systems behind our AI products. You'll 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. You'll 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 You Will 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: Facilitate 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 accommodations@normalcomputing.com. Privacy Notice By submitting your application, you agree that Normal Computing may collect, use, and store your personal information for employment-related purposes in accordance with our Privacy Policy.

## About Normal Computing Corporation

## Company Overview
- **One-liner**: Normal Computing builds AI-accelerated EDA software and physics-based ASICs to enable ultra-efficient hardware for the AI era.
- **Entity Type**: Private (Series B; total funding $92.5M)
- **Headquarters**: New York, New York, USA
- **Founded**: 2022
- **Founders**: Faris Sbahi (CEO), Matthias Tan (Co-Founder), and team of former Google Brain/Google X engineers and scientists

## Core Business
- Primary industry: Semiconductor design (EDA) and custom silicon (ASICs), powered by AI and probabilistic computing.
- Target customers: Large semiconductor design and manufacturing institutions (B2B, enterprise).
- Mission: "Rewriting AI foundations to advance the frontier of reasoning and reliability in the physical world" and enabling a virtuous cycle of self-improving AI hardware.

## Products & Services
- **[Normal EDA](https://normalcomputing.com/)**: An AI-driven electronic design automation platform that understands design intent from specification documents, generates hierarchical test plans with traceability, creates SystemVerilog stimulus, runs simulations, and tracks coverage. It continuously learns from team feedback to accelerate verification for complex chip designs.
- **[Normal ASICs](https://normalcomputing.com/)**: Physics-based custom ASICs that relax traditional computing assumptions (stochastic, stateful, asynchronous) to unlock orders-of-magnitude more efficient compute. Designed to converge hardware with the physical dynamics of AI models.

## Market Standing
- **Valuation/Market Cap**: Not publicly disclosed.
- **Key Metric**: **Total Funding** – $92.5M across multiple rounds (Seed, Venture, Grant, Series B). Notable recent round: $50M led by **Samsung Catalyst** in March 2026 [normalcomputing.com](https://normalcomputing.com/).
- **Notable Investors**: Samsung Catalyst Fund, Intel Ignite, First Spark Ventures, Celesta Capital, ARIA. Also partners with Fraunhofer IESE (DRAMBench benchmark).
- **Growth Signals**: Headcount grew **196.3% YoY** to 54 employees; operates across 6 countries (US, UK, Denmark, Switzerland, India, Canada); actively building open-source tools (e.g., a Verilog simulator built with AI: 580K lines in 43 days).

## Competitive Advantages
- **Physics-First Approach**: Unlike traditional digital logic, Normal’s ASICs embrace stochastic, stateful, and asynchronous computing – aligning hardware with the physics of AI models for dramatic efficiency gains.
- **Full-Stack Co-Design**: The combination of AI-native EDA tools and custom silicon creates a closed loop where software and hardware are co-optimized, shortening time-to-market and enabling workload-specific ASICs.
- **Deep AI Heritage**: Founders and team hail from Google Brain and Google X, bringing deep expertise in probabilistic ML, quantum AI, and physical-world reasoning.

## Strategic Focus
- **Scaling EDA Adoption**: Expanding Normal EDA’s use among top semiconductor companies to "make chip design look more like software".
- **AI Hardware Energy Crisis**: Tackling soaring power demands of AI by delivering ultra-efficient ASICs that can be produced for every workload.
- **Open-Source & Research**: Building community trust through open benchmarks (DRAMBench) and tools (CIRCT-based verification), while advancing formal methods and AI-driven simulation.

## Why Work Here
- **Hybrid Workspace**: Flexible in-office collaboration at offices in **New York (Flatiron HQ)**, **San Francisco**, **London**, and **Copenhagen**. In-person collaboration is valued but with flexibility; free lunch, snacks, and beverages in office.
- **Lean, High-Impact Team**: Small team (54 employees) where every member drives significant impact, works directly with customers, and owns meaningful parts of the product.
- **Interdisciplinary Challenges**: Work spans AI, probabilistic software, hardware, physics, and full-stack engineering – ideal for curious, passionate problem-solvers.
- **Strong Growth Trajectory**: Rapid headcount growth (+196% YoY), recent $50M Series B, and partnerships with industry giants signal a well-funded, high-potential startup.

## Sources
1. [normalcomputing.com](https://normalcomputing.com/)
2. [normalcomputing.com/about](https://normalcomputing.com/about)
3. [linkedin.com/company/normal-computing-corporation](https://www.linkedin.com/company/normal-computing-corporation)
4. [builtin.com/company/normal-computing](https://builtin.com/company/normal-computing)
5. [jobs.ashbyhq.com/normalcomputing](https://jobs.ashbyhq.com/normalcomputing)

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