---
title: 'Software Engineer, Terminal Interface at Normal Computing Corporation'
canonical: 'https://feeny.ai/job/software-engineer-terminal-interface-normal-computing-corporation-new-york-4wm9d2tfm0ja'
type: 'job'
last_seen: '2026-09-10'
---

# Software Engineer, Terminal Interface at Normal Computing Corporation

- **Company:** Normal Computing Corporation
- **Location:** New York, NY
- **Employment:** full-time
- **Work type:** onsite
- **Posted:** 2026-09-02
- **Last confirmed live:** 2026-09-10
- **Apply:** https://jobs.ashbyhq.com/normalcomputing/13a520a8-f9d8-486a-943a-ad1d7665cece

## 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

Normal CLI is how semiconductor engineers do AI-assisted verification work. It is a large interactive terminal application, built in Python and Textual, that design verification engineers keep open all day, usually in environments we do not control: remote workstations inside chip companies, SSH sessions, tmux, Windows and WSL. Our users are accustomed to terminal products, and for many of them this is the first and only surface of Normal they will use. We expect that to remain true. We are hiring the engineer who will own it as a product: productionizing what began as a research tool and giving it a dedicated end-user focus. You will own the interaction model and the information design — how people enter and edit instructions, how a long agent run stays legible while it streams, how tool use and proposed changes are presented for review, and how work is interrupted, resumed, and recovered after a failure. You will also own the local session client beneath it, and be a leading voice in the client API the rest of our product is built on. The boundaries matter here. Our ML and research engineers keep the harness — the skills, tools, hooks, and model behavior that make the agent good at chip verification. You take the application those capabilities reach users through. You will sit on the product engineering team that also builds our desktop workbench, our web product, and our agent orchestration, so the terminal moves into the same product as everything else, with the same vocabulary, state, and quality bar. On any given day, you might rework how a long verification run folds and summarizes itself so an engineer can read it at a glance, chase down why text input breaks under one customer's terminal and IME combination, turn a recurring support thread into a reusable component and a snapshot test, or push back on a runtime event shape that cannot be rendered well.

## What You Will Own

- The terminal application: Information architecture and interaction across commands, navigation, input and editing, streamed output, progress, review, interruption, recovery, empty states, and errors that tell the user what to do next.
- Cross-platform behavior: Correct, fast behavior across terminals, shells, multiplexers, remote sessions, macOS, Linux, Windows and WSL, non-English input and IMEs, and constrained customer environments.
- The client boundary: The local session client, and a leading voice in the structured-event interface it consumes. You shape what the runtime emits so the UI does not have to infer intent from formatted text.
- Standards other contributors build against: Define the command, picker, progress, output, and review patterns that research and product engineers use when they add domain workflows, and keep the experience coherent as they do.
- Responsiveness under load: Streaming, cancellation, concurrency, and event-loop behavior for work that runs for a long time and must stay interruptible and understandable throughout.
- A coherent product across surfaces: Shared terminology, state, authentication, and handoffs between the terminal and the rest of our EDA product, so users moving between them do not have to learn two systems.
- Architecture: Evolve a large Textual application toward reusable components and a clear line between product UI, domain logic, and runtime concerns.
- Confidence to change it: Snapshot and visual-regression coverage, packaging, installation, self-update, and the tests that make it safe to change an interactive application people depend on.

What Makes You a Great Fit

- 4+ years of software engineering experience, including significant time building and maintaining an interactive terminal application, TUI, or comparably rich local client — not command wrappers.
- Experience taking on an existing codebase and improving it without breaking what already worked.
- Familiarity with what makes terminal software hard: keyboard and text input, rendering performance, inconsistent terminal capabilities, process and signal handling, and behavior that differs across platforms and environments.
- Strong engineering fundamentals. The application is written in Python and Textual; we weigh depth and judgment above prior experience with either.
- Experience with event-driven or asynchronous applications: streaming data, local processes, cancellation, concurrency, persistence, and recovery from partial failure.
- A high bar for interface details — defaults, error messages, empty states, wording — and a habit of fixing them before users report them.
- The ability to debug across boundaries, from a keystroke in a terminal emulator through the application to the runtime.
- Experience testing interactive software, and judgment about which behavior is worth pinning down.
- Comfort working with researchers and domain experts, and the ability to learn an unfamiliar technical domain well enough to represent an expert workflow accurately.
- Pragmatic judgment about when to invest in a durable abstraction and when to ship the straightforward version.

Bonus Points Experience with any of the following is helpful, but not required:

- Textual, Rich, prompt-toolkit, curses, Bubble Tea, Ratatui, Ink, or another terminal UI framework
- PTYs, terminal emulation, multiplexers, or remote shell and host abstractions
- Designing human-in-the-loop experiences for coding agents, AI tools, or other long-running automated systems
- Cross-platform packaging, self-update systems, internationalization, IME support, or visual regression testing
- Electron or another desktop framework, particularly embedding a CLI, TUI, or agent runtime
- Semiconductors, EDA, or hardware engineering workflows

## 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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