Backend Software Engineer, Normal Computing
$150-250k
Offers Equity
Generative AI for enterprise
Be an early applicant
Generative AI for enterprise
21-100 employees
Be an early applicant
$150-250k
Offers Equity
21-100 employees
Company mission
To bridge artificial intelligence to the most sensitive industrial and advanced manufacturing applications around the globe.
Role
Who you are
- Previous experience with the semiconductor or hardware industry is valued, but not required
- We're hiring engineers who are passionate about solving real-world problems in complex, technical domains and building systems that empower users to work optimally
- If you're motivated to develop reliable, performant systems and design intuitive experiences for AI-powered workflows, this role offers the opportunity to make a significant impact on how an entire industry works
- 5-8 years of software engineering experience, with a strong focus on building reliable, scalable systems as well as shipping end to end features Experience as a former zero-to-one engineering lead or startup founder is highly valued
- Experience building complex systems with a strong intuition for reliability, performance, and maintainability. You avoid the failure mode of shipping features quickly without ensuring the system design and implementation are truly excellent
- Experience working with LLMs or building AI-powered applications. You're excited about understanding the nuances of different model paradigms (agents, multimodality, simulation methods) and how to design product experiences that augment rather than detract from user workflows
- Proven ability to learn continuously, work independently, and make decisions with minimal supervision. You deliver on your commitments, value outcomes, and adapt quickly when priorities shift
- Skill and comfort working in a constantly evolving environment with dynamic objectives and iteration with users
Desirable
- Experience building IDE extensions, developer tools, or design-to-code systems
- Meaningful experience working and building within or for the semiconductor industry, or developing hardware products or software for hardware products
What the job involves
- As a Software Engineer focused on product engineering in Normal EDA, you will be responsible for building the systems and workflows used by hardware engineers to build and verify the chips that power modern AI
- You'll regularly be faced with sophisticated technical problems at the intersection of AI and product engineering, requiring you to scope out solution designs and find incremental paths to shipping new features
- As part of this, you will own APIs and schemas that power core product functionality, collaborating closely with other engineers in developing them
- Building complete, integrated prototypes that bring AI capabilities to life in production-grade services, and polished frontend interfaces to create working V0s that users can actually test and the ML team can validate
- Architecting and developing backend systems that support complex verification workflows
- Owning API contracts between frontend and backend systems
- Driving engineering roadmaps in collaboration with researchers, hardware experts, and product managers to discover and propose features that drive user stickiness
Our take
As the rate of AI adoption accelerates, Normal Computing is positioning itself to make advanced AI more usable and scalable for enterprises, where ris,, reliability and energy constraints remain major barriers. While generative AI has so far flourished in consumer settings, enterprise use has lagged due to concerns around control, auditability and cost. Normal's approach hopes to unlock these more complex use cases by rethinking how AI systems are built and deployed from the ground up.
At the core of the company's strategy is its Probabilistic AI framework, which gives customers greater control over reliability, adaptivity and auditability when working with private data. This software vision is now being reinforced by a major hardware milestone: the successful tape-out of CN101, the world's first thermodynamic computing chip. By harnessing natural physical dynamics such as stochasticity and noise, CN101 is designed to dramatically improve energy efficiency on AI and scientific workloads, allowing tasks like complex underwriting, probabilistic sampling and large-scale optimization to run faster and within fixed data centre energy budgets.
By tackling both the trust and energy bottlenecks that limit enterprise AI adoption, Normal is expanding its ambition from AI software into next-generation compute infrastructure. With a clear roadmap from CN101 to more advanced chips over the next few years, and substantial funding behind its R&D efforts, the company has the potential to play a meaningful role in shaping how high-performance AI scales in practice.
Freddie
Company Specialist at Welcome to the Jungle
Company
Funding (last 2 of 3 rounds)
Nov 2024
$68m
GRANT
Jun 2023
$8.5m
SEED
Total funding: $85m
Company HQ
Civic Center, New York, NY
Leadership
Faris Sbahi
(Co-Founder & CEO)Previously worked as a Research Scientist at X, the moonshot factory, a Software Engineer at Google, and as a Forward Deployed Engineer at Palantir Technologies.
Matthias Tan
(Co-Founder & COO)Venture Partner at NextGen Venture Partners. Former Principal of Strategy and Partnerships at X, the moonshot factory, and Director of Product and Partnerships at Pony.ai.
Share this job
View 9 more jobs at Normal Computing