Senior/Principal Lead Delivery Engineer
No salary listed
Senior, Expert
Master's, PhD
San Mateo, CA, USA
In Person
Solution EngineeringImplementation & Technical Account Management
About the job
Requirements
- 5–10 years of experience in a technical role in a relevant industry, such as engineering, simulation, research and development, advanced engineering, technical program management, or applied artificial intelligence and machine learning. Principal-level candidates need an extensive industry track record.
- Multi-physics fluency across industrial engineering disciplines, including structural mechanics, thermal analysis, electromagnetics, rotating machinery, fluid dynamics, or multi-physics optimization; generalist depth across several disciplines is more valuable than world-class depth in one.
- Strong hands-on engineering skills in Python, scripting, simulation tools, and artificial intelligence and machine learning workflows, with comfort working directly in code, models, or simulation setups.
- Working knowledge of artificial intelligence and machine learning applied to engineering, such as surrogate modeling, neural operators, physics-informed machine learning, or digital twins.
- Ability to lead cross-functional technical teams without direct authority and influence through clarity, credibility, and outcomes.
- Track record of choosing appropriate problems to solve and shipping things that get used, rather than only producing demonstrations.
- Ability to explain a physics model to a chief engineer and present a customer roadmap to company leadership.
- Comfort with ambiguity and persistence through iteration, with ability to question requests and prioritize work that has the greatest impact.
- Willingness to travel 10–25% to customer sites.
Responsibilities
- Own end-to-end customer outcomes across new and existing industrial accounts, from discovery and use-case scoping through model development, deployment, and integration into customer engineering workflows.
- Author Statements of Work, educate customers about engagement plans, and own delivery accountability against those plans.
- Lead a matrixed value delivery team of Applications Engineers, Applied AI/ML Scientists, Data and Platform Engineers, and selected product engineers; set technical direction, sequence work, and remove blockers.
- Operate as both project manager and product manager by running sprints, milestones, and risk while selecting use cases and shaping product direction.
- Stay hands-on by debugging models, restructuring data pipelines, and prototyping workflow integrations as needed.
- Co-engineer with industrial engineers on use-case development, sharing knowledge and building trust through collaborative work.
- Partner with the go-to-market team on new account engagement, handoff from go-to-market to delivery, and account growth.
- Bring market and customer feedback to Product and Research and shape the roadmap for industrial use cases.
Desired Qualifications
- An advanced degree (Master of Science or PhD) in Mechanical, Industrial, Manufacturing, Electrical, or Materials Engineering.
- Prior experience at major industrial companies or enterprise software companies serving industrial sectors.
- Experience with engineering challenges specific to rotating machinery, heat exchangers, pumps and compressors, or similar complex engineered products.
- Track record of driving technology adoption in industrial environments with measurable business impact, such as reduced development time, improved performance, or lower prototyping costs.
- Experience deploying machine learning or simulation tooling into production engineering workflows.
About the company
Luminary Cloud offers a software-as-a-service platform that provides high-performance computing for industrial R&D. It delivers an interactive simulation, visualization, and analysis toolkit that achieves near-supercomputer performance without requiring expensive on-site hardware. Through a subscription model, customers gain ongoing access and updates, avoiding large capital investments in HPC infrastructure. The company focuses on aerospace, automotive, and advanced manufacturing, differentiating itself with strong performance, automation, and cloud scalability backed by expertise in computational physics and cloud computing.
Company Size
51-200
Company Stage
Series B
Total Funding
$187M
Headquarters
Palo Alto, California
Founded
2019
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Simplify's Take
What believers are saying
- Northrop Grumman and NVIDIA collaborations validate Luminary's product and shorten enterprise sales cycles.
- SHIFT-Crash and new defense models expand usage from wings into crash, submarines, and pumps.
- Onshape integration and private-cloud launches broaden distribution and unlock regulated buyers.
What critics are saying
- Luminary reported about 62 employees in March 2026, down from 87 in 2023.
- The company still lacks announced hardware wins from Northrop Grumman, despite 2025 collaboration.
- Defense-heavy positioning creates procurement concentration; one lost program can crater revenue quickly.
What makes Luminary unique
- Physics AI models predict engineering outputs in seconds across aerospace, automotive, and defense.
- NVIDIA GeoTransolver and PhysicsNeMo anchor Luminary's technical stack and credibility.
- Private Cloud supports air-gapped deployments for ITAR-restricted defense and aerospace customers.
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Benefits
- Hybrid Work Options