Job Description:
The Staff Electrical Engineer leads the design, integration, and validation of advanced automotive electrical and electronic architectures that enable autonomous driving capabilities. This role focuses on modeling and maintaining the vehicle’s electrical architecture, integrating off-the-shelf sensors and AI compute platforms, and ensuring robust, safe, and compliant operation of high-speed networks and power distribution systems across the vehicle.
Responsibilities:
-
Model and maintain the vehicle’s electrical architecture and logical connectivity using advanced E/E architecture tools.
-
Author RFI and RFP packages to evaluate Tier-1 and Tier-2 suppliers for autonomous driving computing platforms and perception sensors.
-
Drive the electrical and logical integration of off-the-shelf sensors and autonomous driving compute units into the vehicle platform.
-
Manage signal integrity and channel budgets for high-speed camera networks (GMSL and FPD-Link) over coaxial and shielded twisted pair cabling.
-
Design multi-gigabit Automotive Ethernet networks connecting off-the-shelf sensors and compute modules.
-
Formulate and validate vehicle-wide time synchronization protocols (including IEEE 802.1AS and gPTP) across all autonomous driving nodes.
-
Architect redundant, fail-operational power distribution networks for safety-critical autonomous driving actuators.
-
Enforce system-level EMI and EMC mitigation strategies and review supplier compliance reports to ensure electromagnetic compatibility.
-
Synthesize supplier safety cases into the vehicle-level ISO functional safety framework.
-
Define hardware-level diagnostic mechanisms to monitor component health and trigger safe-stop fallback strategies.
-
Collaborate closely with mechanical packaging teams to define sensor placement, fields-of-view, and vehicle calibration strategies.
-
Lead root-cause investigations of complex, intermittent electrical failures and sensor dropouts identified during fleet testing.
-
Audit supplier-provided schematics and hardware designs to identify architectural shortcomings, boundary-case vulnerabilities, and non-compliance with vehicle requirements.
-
Architect the vehicle’s logical network topology, including static IP assignment schemes, subnet routing paths, and network switch configurations.
-
Design and document end-to-end network traffic paths, mapping individual sensor data streams such as LiDAR UDP packets and ROS messages to target compute nodes and subnets.
Skills:
-
8+ years of experience in automotive E/E architecture design or vehicle-level electrical systems engineering, with a focus on ground-up vehicle development.
-
Bachelor’s or Master’s degree in Electrical Engineering, Mechatronics, or a related technical discipline.
-
Proven proficiency with E/E architecture tools such as Zuken E3.series, Siemens Capital, or equivalent system modeling software.
-
Deep understanding of electrical architecture, including signal integrity, high-speed Automotive Ethernet, CAN, GMSL, and PCIe bus technologies.
-
Technical understanding of high-speed serializer/deserializer protocols such as GMSL2/3 and FPD-Link III/IV.
-
Strong working knowledge of multi-gigabit Automotive Ethernet networks.
-
Strong working knowledge of standard in-vehicle networks, including CAN FD, LIN, and PCIe, as well as related network debugging tools.
-
Demonstrated experience reviewing supplier hardware specifications, conducting circuit analysis, and assessing compatibility of off-the-shelf components.
-
Familiarity with component and system-level electromagnetic compatibility testing and validation standards such as CISPR 25 and relevant ISO EMC standards.
-
Practical understanding of ISO functional safety concepts up to ASIL-D.
-
Understanding of automotive cybersecurity principles as they relate to vehicle electrical and network architectures.
-
Experience designing or integrating redundant, low-voltage power distribution networks (12V/24V) and smart electronic fusing architectures.
-
Proven capability to critically analyze third-party electrical schematics, PCB layouts, and block diagrams to enforce design robustness.
-
Ability to integrate AI compute platforms into automotive vehicle electrical architectures.
Additional Skills & Qualifications:
-
Experience working with autonomous driving computing platforms and perception sensor suites.
-
Experience in defining and validating vehicle-wide time synchronization protocols such as IEEE 802.1AS and gPTP.
-
Experience with system-level EMI and EMC mitigation techniques and supplier compliance review.
-
Familiarity with diagnostics strategies for monitoring component health and implementing safe-stop fallback mechanisms.
-
Experience collaborating with cross-functional teams, including mechanical packaging and calibration teams, to optimize sensor placement and coverage.
-
Experience leading complex root-cause investigations for intermittent electrical and network-related issues in fleet or vehicle test environments.
-
Strong analytical and problem-solving skills applied to large-scale, safety-critical vehicle systems.
-
Ability to document architectures, network topologies, and data flows clearly for both technical and non-technical stakeholders.
Job Type & Location
This is a Contract to Hire position based out of Mountain View, CA.
Pay and Benefits
The pay range for this position is $70.00 - $80.00/hr.
Eligibility requirements apply to some benefits and may depend on your job classification and length of employment. Benefits are subject to change and may be subject to specific elections, plan, or program terms. If eligible, the benefits available for this temporary role may include the following:
- Medical, dental & vision
- Critical Illness, Accident, and Hospital
- 401(k) Retirement Plan – Pre-tax and Roth post-tax contributions available
- Life Insurance (Voluntary Life & AD&D for the employee and dependents)
- Short and long-term disability
- Health Spending Account (HSA)
- Transportation benefits
- Employee Assistance Program
- Time Off/Leave (PTO, Vacation or Sick Leave)
This is a fully onsite position in Mountain View,CA.
Application Deadline
This position is anticipated to close on Jul 14, 2026.
About Actalent
Actalent is a global leader in engineering and sciences services and talent solutions. We help visionary companies advance their engineering and science initiatives through access to specialized experts who drive scale, innovation and speed to market. With a network of almost 20,000 consultants and 5,000 clients across the U.S., Canada, Asia and Europe, Actalent serves many of the Fortune 500. We are proud to be an Engineering News-Record (ENR) Top 500 Design Firm for our engineering design services and a ClearlyRated Best of Staffing® winner for both client and talent service.
The company is an equal opportunity employer and will consider all applications without regard to race, sex, age, color, religion, national origin, veteran status, disability, sexual orientation, gender identity, genetic information or any characteristic protected by law.
If you would like to request a reasonable accommodation, such as the modification or adjustment of the job application process or interviewing process due to a disability, please email [email protected] for other accommodation options.
San Francisco Fair Chance Ordinance: Pursuant to the San Francisco Fair Chance Ordinance, for all positions located in the city and county of San Francisco, we will consider for employment qualified applicants with arrest and conviction records.
Massachusetts Lie Detector: It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.
Use of Artificial Intelligence (AI): We may use Artificial Intelligence (AI) to support parts of our hiring process, including sourcing, screening, and evaluating candidates. AI helps assess applications and qualifications, but final decisions are made by our hiring team. By applying, you acknowledge and agree that your application may be reviewed using AI tools.
