Neural Concept
Founded in 2019, Neural Concept builds the intelligence layer for engineering software, enabling companies to design and develop complex products faster and more efficiently. Its AI-first engineering platform embeds physics-aware intelligence directly into design and simulation workflows, allowing engineering teams to move beyond isolated tools and manual iteration toward continuous, AI-augmented decision-making. The company drives product development across major industries, including automotive, aerospace, energy, consumer electronics, semiconductors and defense, working with the world’s leading global OEMs and component suppliers. Neural Concept is headquartered in Switzerland, with a growing global presence including offices in Munich, New York and the Asia-Pacific region and is backed by global investors, including Goldman Sachs, Forestay Capital and D. E. Shaw Group.
Open Positions at Neural Concept
5 open positions
Build customer-specific integrations and automate complex PLM, CAD, and simulation workflows while feeding field insights back into NC’s core product. This customer-facing role combines production software engineering, engineering-domain expertise, and hands-on on-site collaboration.
Serve as the technical and strategic advisor for Japanese engineering customers, connecting CAD/CAE challenges to Neural Concept’s AI platform. Lead discovery, demos, solution roadmaps, Statements of Work, adoption, and expansion in collaboration with Sales and engineering teams.
Neural Concept is seeking a customer-facing Solution Engineer to translate engineering challenges into credible AI solutions, lead discovery and demos, and guide accounts from pre-sales through expansion. The role combines engineering expertise, strategic consulting, and commercial influence across aerospace, automotive, and advanced manufacturing clients.
Own and expand automated testing and quality practices for an enterprise-grade technical platform. You’ll combine QA expertise, Python and Playwright automation, performance testing, and emerging AI tools to improve release reliability.
Help engineering leaders transform product-design workflows by applying machine learning, deep learning, and Python to complex engineering data. This customer-facing role combines technical delivery, proofs of concept, training, and collaboration on product improvements.