Sr. ADAS/AD Systems and Integration Engineer

Lucid Motors • Southfield, MI

2d

About The Position

Lucid’s Autonomous Driving and ADAS organization develops and integrates next-generation autonomy features into Lucid vehicles. The Sr. ADAS/AD Systems and Integration Engineer owns assigned features from concept and requirements through integration and production readiness, with a primary focus on supervised point-to-point driving (L2++) and work that also contributes to L4 automated driving. This is a hands-on individual-contributor role connecting vehicle systems, autonomy software, safety, and validation. The engineer translates product goals into implementable specifications, investigates real-world behavior, and drives technical decisions across teams.

The role defines feature use cases, operating conditions, operational design domains, behavioral requirements, limitations, and measurable acceptance criteria. It decomposes vehicle-level objectives into functional, performance, and safety requirements; allocates performance budgets; and maintains traceability through implementation and verification. It also develops functional architectures, state machines, interface specifications, and hardware/software ownership boundaries, while evaluating trade-offs involving sensors, compute, latency, vehicle interfaces, and algorithm capability.

The engineer specifies feature activation, availability, mode transitions, driver interaction, fault response, and degraded behavior, distinguishing L2 driver-supervision responsibilities from L4 system responsibilities, including fallback and minimal-risk behavior where applicable. The role works across autonomy, vehicle integration, and HMI teams to resolve dependencies; defines scenario-based verification and validation across simulation, software- and hardware-in-the-loop, proving-ground, and on-road testing; and connects requirements to test methods and objective pass/fail criteria.

The engineer also establishes feature metrics, logging needs, scenario coverage, and dataset representativeness with data and test teams; uses fleet and test data to identify gaps; investigates failures and performance limits; drives root-cause resolution and regression coverage; and collaborates with functional safety and SOTIF engineers on hazards, foreseeable misuse, triggering conditions, safety mechanisms, standards, and regulatory requirements. The role leads technical reviews within its scope and coordinates with program teams, suppliers, and technology partners to support integration and evidence-based release decisions.

Requirements

• Bachelor's degree in electrical, mechanical, automotive, aerospace, or computer engineering, computer science, robotics, or a related discipline, or equivalent practical experience.
• At least 6 years of relevant engineering experience, including hands-on systems ownership for ADAS, automated driving, or similarly complex safety-critical vehicle or robotics systems.
• Experience taking a feature through requirements, architecture, integration, and verification, with clear examples of technical decisions and issues personally resolved.
• Working knowledge of the autonomy stack and vehicle-level interactions, including sensor and compute limitations, perception/planning/control interfaces, timing, diagnostics, and degraded operation.
• Ability to write testable requirements, define interfaces and acceptance criteria, manage traceability, and use scenario-based testing and quantitative analysis to assess system behavior.
• Practical programming and data-analysis skills in Python or C++.
• Confidence interpreting logs, navigating software, using Vector tools such as CANalyzer, and debugging integrated systems.
• Working knowledge of functional safety (ISO 26262) and safety of the intended functionality (ISO 21448/SOTIF), with the ability to collaborate effectively with safety specialists.
• Strong technical communication and cross-functional problem-solving skills; ability to own a defined scope, document assumptions, and drive alignment without direct authority.

Nice To Haves

• Experience working on supervised point-to-point driving (L2++) or L3/L4 autonomy.
• Experience with learned or end-to-end driving approaches and modular autonomy stacks, including how their limitations and trade-offs affect requirements, observability, and validation.
• Hands-on vehicle integration; experience with automotive networks such as CAN and Ethernet, and sensor/compute integration, synchronization, diagnostics, or redundancy.
• Experience with large-scale scenario mining, simulation evaluation, fleet-data analytics, SQL, or statistical methods for evaluating rare events and coverage.
• Experience with requirements and architecture tools such as Jama, DOORS, or SysML/MBSE, supplier interfaces, release readiness, or applicable NCAP and UNECE requirements.

Responsibilities

• Own systems definition and delivery of assigned driving features, including use cases, operating conditions, ODD, behavioral requirements, limitations, and measurable acceptance criteria.
• Decompose vehicle-level objectives into functional, performance, and safety requirements; allocate performance budgets and maintain traceability from stakeholder needs through implementation and verification evidence.
• Develop functional architectures, state machines, interface specifications, and hardware/software ownership boundaries; evaluate trade-offs involving sensors, compute, latency, vehicle interfaces, and algorithm capability.
• Specify activation, availability, mode transitions, driver interaction, fault response, and degraded behavior, distinguishing L2 driver-supervision responsibilities from L4 system responsibilities.
• Partner with perception, localization, prediction, planning, controls, embedded software, vehicle integration, and HMI teams to resolve dependencies and deliver coherent end-to-end behavior.
• Define scenario-based verification and validation strategies across simulation, software-/hardware-in-the-loop, proving-ground, and on-road testing, linking requirements to test methods and pass/fail criteria.
• Establish feature metrics, logging needs, scenario coverage, and dataset representativeness with data and test teams; use fleet and test data to identify gaps and prioritize improvements.
• Investigate failures and performance limitations using vehicle logs, software behavior, and targeted experiments; drive root-cause resolution, regression coverage, and release-change assessments.
• Collaborate with functional safety and SOTIF engineers on hazard analysis, foreseeable misuse, triggering conditions, safety mechanisms, and supporting evidence; incorporate relevant standards and regulatory requirements.
• Lead technical reviews within feature scope, communicate risks and trade-offs, and coordinate with program teams, suppliers, and technology partners to support integration and evidence-based release decisions.

Benefits

• Medical, dental, and vision insurance
• Life and disability coverage
• Paid time off
• Paid holidays
• Paid sick leave
• 401(k) retirement plan
• Eligible employees may participate in the company's equity program and/or a discretionary annual cash incentive program

What This Job Offers

• Job Type: Full-time
• Career Level: Senior