Jobs at Neural Concept

As VP of Engineering, you will lead a high-performing software engineering team, ensuring quality delivery, structuring the organization, establishing modern processes, and collaborating closely with leadership and clients.

As an ML Application Engineer, you'll analyze engineering data, develop ML solutions, and train customer teams for AI adoption, working closely with engineering clients to enhance product design workflows using advanced technologies.

Own full enterprise sales cycle for Engineering AI platform in Sweden, building territory strategy, generating pipeline, leading multi-stakeholder deals, creating business cases, negotiating contracts, and coordinating cross-functional teams to close and expand strategic accounts.

Drive pre-sales and account technical strategy for Neural Concept's Engineering AI platform: lead discovery, craft tailored demos, define technical roadmaps and SOWs, run steering committees, drive adoption and expansion, and collaborate with Sales, Forward Deployed Engineering, Product and R&D. Requires engineering credibility and fluency in Korean and English.

Drive the full pre-sales technical motion: discover customer needs, design AI-enabled engineering solutions, deliver tailored demos and Statements of Work, guide account technical strategy, support adoption and expansion, and collaborate with sales, delivery, and product teams to align roadmap and deployments.

Own full enterprise sales cycle for Engineering AI platform: prospecting, account strategy, discovery, negotiation, closing, and expansion. Build relationships with engineering, IT, procurement, and executives; coordinate cross-functional teams; create business cases and commercial proposals; maintain pipeline and forecasts; represent company at customer meetings and events.

Sell an Engineering AI platform to enterprise engineering-led companies. Own full sales cycle from prospecting to closing, build account strategies, engage stakeholders across engineering, IT and executives, create business cases, lead negotiations, coordinate cross-functional teams, maintain pipeline and represent the company at events.

Lead pre-sales technical engagements for an Engineering AI platform: run discovery, craft demos, define technical roadmaps and SOWs, drive adoption and expansion, and liaise between Sales, Forward Deployed Engineering, Product and R&D to translate engineering workflows into AI-enabled solutions.

You will leverage your technical expertise and sales leadership to drive revenue growth, build partnerships, and represent technology to engineering companies, focusing on capturing new business opportunities in Europe.

The Account Executive will leverage technical expertise in enterprise SaaS sales to drive revenue growth, build partnerships, and represent Neural Concept's technology in engineering sectors.

The role involves engaging with customers, translating insights into product requirements, and collaborating across departments. The candidate should have engineering experience and strong product instincts to manage a product discovery process.

Own revenue forecasting, GTM analytics, RevOps tech stack, and sales process design. Partner with Finance and Sales to build commercial infrastructure, drive forecasting accuracy, automate workflows, and deliver executive-ready insights to improve pipeline velocity and revenue outcomes.

The Consumer Electronics Solution Owner will lead the development of engineering workflows for the consumer electronics industry, partnering with customers to define solutions and ensure value delivery.

The Technical Account Manager will drive customer success, manage accounts, deliver onboarding and demos, and align engineering solutions with customer needs.

Lead technical pre-sales on strategic accounts across DACH & Nordics: run discovery, define AI transformation roadmaps, deliver client-tailored demos and Statements of Work, grow the regional SE team, and partner with Sales, FDE, Product and R&D to close and scale multi-year engagements.

As a Technical Account Manager, you'll drive customer adoption of AI tools, manage projects, deliver demos, and advocate for user feedback while collaborating across teams to ensure customer success.

Drive pre-sales technical engagement: discovery, tailored demos, define AI strategies and SOWs, run steering committees, enable user adoption, identify upsell opportunities, and bridge Sales, Forward Deployed Engineering, Product and R&D.

Own end-to-end product lifecycle for a vertical engineering solution: run customer discovery, define and prioritize requirements, prototype with AI-assisted tools (including scripting), lead cross-functional CAD/CAE/ML engineering teams to production, and track adoption and value delivery to inform the global roadmap.

Lead the design and delivery of AI-driven engineering workflows. Collaborate with product managers, customers, and engineers to standardize components and drive adoption across platforms.

The ML Application Engineer will work with customers to apply machine and deep learning to engineering challenges, develop solutions using Python, and train customer teams in AI adoption.