Top Tech Jobs & Startup Jobs

Owns end-to-end manufacturing execution and operational bring-up for complex physical hardware, from prototype builds through validation and commercial launch. Responsibilities include managing build schedules, EVT/DVT/PVT milestones, contract manufacturers, suppliers, BOM risks, DFM/DFA, cost and tooling budgets, factory line bring-up, quality and yield, ECOs, root-cause analysis, and field readiness.

Drive end-to-end manufacturing execution and new product introduction for physical AI hardware. Oversee contract manufacturers, optimize assembly and test operations, perform DFM/DFA/DFT reviews, establish tooling and production documentation, troubleshoot assembly failures, conduct root cause analysis, improve yields, and transition prototypes into scalable volume production. Collaborate with design, quality, supply chain, vendors, and enterprise customers.

Advise Applied Intuition’s U.S. and international defense business on government contracts, procurement laws, data rights, IP, export controls, CUI, compliance, and international bids. Negotiate prime contracts, subcontracts, supplier agreements, software licenses, and teaming agreements. Support proposals, legal operations, investigations, policy development, training, and scalable compliance programs while partnering with product, engineering, finance, sales, and marketing teams.

Develop and integrate autonomy and drive-by-wire systems across software, hardware, and mining vehicle platforms. Responsibilities include designing sensors and actuators, embedded application development, firmware and mechatronics troubleshooting, system debugging, telemetry analysis, customer-site integration, operating-procedure development, and technical coordination with hardware and firmware teams. The role requires field work, customer interaction, and international travel.

Develop and integrate embedded vehicle software across workstation, SIL, HIL, and target hardware. Own customer integration projects, integrate AUTOSAR software components and ARXML against generated RTE contracts, collaborate across software and hardware teams, and troubleshoot system reliability issues. The role requires embedded C/C++, electronic systems debugging, Linux, and Bash, with automotive protocols, AUTOSAR, Python, and CI/CD experience preferred.

Build and own hardware simulation capabilities for vehicle programs. Define load cases, select CAE tools, perform structural, modal, vibration, fatigue, and thermal analyses, and correlate simulations with physical tests. Establish scalable CAE processes, manage external engineering contractors, collaborate with mechanical design and validation teams, and mentor engineers while setting simulation quality standards.

Own the software release management lifecycle for autonomous trucking products, including release scheduling, build preparation, subsystem integration, testing, troubleshooting, and safe deployment. Coordinate cross-functional teams and developers, oversee integration processes, and align release priorities and schedules with technical program managers. The role requires experience with safety-critical systems, autonomous driving or robotics, release tools, Linux, scripting, and build systems.

Lead global treasury operations, including cash management, liquidity forecasting, banking relationships, FX risk, treasury systems, financing, investments, compliance, and audits. The role partners with Finance, Legal, Accounting, FP&A, and international teams to support government-contracting requirements, entity expansion, and strategic treasury initiatives while providing analytical recommendations to senior leadership.

Leads commercial growth in the automotive vertical by engaging strategic customers, shaping product strategy from industry trends, planning revenue strategy, scoping technical and commercial opportunities, demonstrating solutions, and ensuring successful customer outcomes. Partners closely with go-to-market and engineering teams while managing multiple complex projects and deadlines.

Design and build scalable neural simulation systems that transform real-world driving data into high-fidelity simulation environments and synthetic labeled data. Develop distributed data-processing systems, ML training, evaluation, validation, and inference pipelines, plus storage solutions for multimodal data. Improve reliability, observability, and performance while collaborating with infrastructure, autonomy, research, and product teams.