Full-time position | San Mateo, CA (Onsite)
JOIN THE REVOLUTION IN ENGINEERING INNOVATION
Luminary helps engineering companies be more competitive by getting to market faster, creating better products, and reducing development risk. We do this through our Physics AI platform — the fastest and easiest way to build and deploy models that understand and instantly predict physical reality with precision. Our customers span industries from automotive and aerospace to defense, industrial, semiconductors, and energy — ranging from hyper-growth startups to Fortune 100 enterprises. Luminary is a Series B company headquartered in San Mateo, California.
YOUR IMPACT
As the Senior/Principal Lead Delivery Engineer for Automotive, you own customer outcomes end-to-end for Luminary's engagements with OEMs, Tier-1 suppliers, and EV/ADAS innovators. You are a dual hat — project manager and product manager — leading a value delivery team across Applications Engineering, Applied AI/ML, Data & Platform, and product engineering in a matrix structure. You translate the hardest problems in vehicle design, propulsion, electrification, and manufacturing into Physics AI solutions, and partner with the GTM team on account engagement and growth.
WHAT YOU'LL DO
- Own end-to-end customer outcomes across new and existing automotive accounts — from discovery and use case scoping through model development, deployment, and embedding into customer engineering workflows.
- Author Statements of Work (SOWs), educate customers on the engagement plan, and own delivery accountability against them.
- Lead a value delivery team in a matrix structure: Applications Engineers, Applied AI/ML Scientists, Data and Platform Engineers, and selected product engineers. Set technical direction, sequence the work, remove blockers.
- Operate as a dual hat — project manager and product manager — running sprints, milestones, and risk while also choosing the right use cases and shaping the product intuition for what to build next.
- Stay hands-on-keyboard where it matters. Debug a model, restructure a data pipeline, prototype a workflow integration. Lead from the front, not from slides.
- Embrace co-engineering: work side-by-side with customer engineers on use case development, sharing knowledge and building trust through visible, collaborative work.
- Partner with the GTM team on new account engagement, GTM-to-delivery handoff, and account growth.
- Bring market and customer signal back to Product and Research, directly shaping Luminary's roadmap for automotive use cases.
WHAT YOU BRING
- 5–10 years of experience in a technical role in a relevant industry (engineering, simulation, R&D, advanced engineering, technical program management, or applied AI/ML). Principal-level candidates have an extensive track record in automotive.
- Multi-physics fluency across automotive disciplines: structural mechanics, crash/safety, NVH, thermal management, battery systems, aerodynamics, electromagnetics, or multi-physics optimization. Generalist depth across several disciplines is more valuable here than world-class depth in one.
- Strong hands-on engineering chops — Python, scripting, simulation tools, and AI/ML workflows. Comfortable diving into code, models, or simulation setups when needed.
- Working knowledge of AI/ML applied to engineering — surrogate modeling, neural operators, physics-informed ML, or digital twins.
- Demonstrated ability to lead cross-functional technical teams without direct authority. You influence through clarity, credibility, and outcomes.
- Product instinct: a track record of choosing the right problems to solve and shipping things that get used — not just demos that get cited.
- Customer-facing presence: equally credible explaining a physics model to a chief engineer and walking a customer roadmap with Luminary leadership.
- Self-starter mentality, comfortable with ambiguity, persistent through iteration. You question what you are asked to do and prioritize what actually moves the needle.
- Willing to travel 10–25% to customer sites.
PREFERRED QUALIFICATIONS
- Advanced degree (MS or PhD) in Mechanical, Aerospace, Electrical Engineering, or related field.
- Prior experience at automotive OEMs (e.g., Tesla, Ford, GM, BMW, Volkswagen, Hyundai, Rivian, Lucid), Tier-1 suppliers (e.g., Bosch, Continental, ZF, Magna, Aptiv), or enterprise software companies serving automotive engineering.
- Familiarity with software-defined vehicle (SDV) architectures and how simulation/AI integrates into next-generation vehicle development.
- Track record of deploying ML or simulation tooling into production engineering workflows (not just research demos).
