Staff Vehicle Architecture Engineer

Rivian and Volkswagen Group Technologies • Irvine, CA

1d

About The Position

Rivian and Volkswagen Group Technologies is a joint venture focused on developing technology for software-defined electric vehicles, including operating systems, zonal controllers, cloud, and connectivity solutions. The Vehicle System Architecture team owns vehicle-level mechatronic architecture and translates product intent from Brand Product Definition, Program, Cost Engineering, Manufacturing, Strategy, and Reliability into parts and function distribution across the vehicle, from product concept through manufacturing.

The Staff Vehicle Architecture Engineer builds and owns parametric models that guide architecture decisions, including controller count and placement, function allocation, sensor and actuator distribution, and harness topology. The role runs quantified architecture trade studies and develops cost and bill-of-materials models to evaluate options and identify opportunities to remove unnecessary components. It also analyzes new technology integration using a software and hardware platform design approach.

The engineer develops AI and LLM pipelines for architecture artifacts, such as extracting information from specifications, generating and checking candidate configurations, and identifying gaps across requirements, device lists, and interface definitions. The role deploys semantic search and integrates AI tools into engineering workflows with human-in-the-loop safeguards. It also connects architecture decisions to downstream outcomes, contributes to vehicle-level safety and fault analyses, participates in cross-domain reviews, validates models against vehicle, laboratory, and supplier data, and documents methods for other engineers.

Requirements

• BS or MS in Electrical, Computer, Mechanical, Systems, or Aerospace Engineering, or equivalent demonstrated experience.
• At least 5 years in vehicle, aerospace, or electromechanical systems engineering, or an equivalent record of building analyses that informed real design decisions.
• Strong Python skills in data processing, parametric modeling, automation, and prototyping AI workflows.
• Practical experience building LLM applications, such as RAG pipelines, semantic search, structured extraction, or agent frameworks.
• Ability to decompose a vehicle into subsystems, functions, and interfaces and reason about how changes propagate across them.
• Ability to work with and defend consequential numerical analyses involving cost, mass, and power budgets.

Nice To Haves

• E/E architecture background, including zonal and secondary ECUs, low-voltage power distribution, networks, harness design, CAN/Ethernet, and DBC/ARXML.
• Experience with physical simulation tools such as OpenModelica, Julia, Spice, Modelica, or FMI/FMU co-simulation.
• Worst-case, tolerance, and statistical analysis (WCCA, Monte Carlo, DOE) applied to real designs.
• Hands-on physical-systems projects, such as vehicle dynamics, powertrain, robotics, Formula SAE, Baja SAE, or solar car.
• Manufacturing or design-for-manufacturing exposure.
• GitLab CI/CD experience.
• An AI portfolio applying LLMs or ML to engineering artifacts; academic or personal projects count.
• STPA, DFMEA, or fault tree analysis knowledge.

Responsibilities

• Build and own parametric models supporting vehicle architecture decisions, including controller count and placement, function allocation across zonal and secondary ECUs, sensor and actuator distribution, and harness topology.
• Run architecture trade studies with quantified outcomes for cost, mass, harness complexity, power, temperature and environmental factors, reliability, and manufacturability; provide the model, parameters, and sensitivity analysis for each study.
• Build cost and bill-of-materials models to quantify vehicle architecture options.
• Use models to identify controllers, harness runs, and sensors that can be eliminated before optimizing the remaining design.
• Analyze integration of new technologies using a software and hardware platform design approach.
• Build LLM and agentic pipelines to extract device and interface data from specifications, generate and check candidate architecture configurations, and identify gaps across requirements, device lists, and interface definitions.
• Deploy semantic search across requirements, architecture models, device data, and prior trade studies.
• Integrate AI assistance into the team's toolchain, including Flow Engineering, Airtable, and GitLab, using APIs and CI pipelines with human-in-the-loop safeguards.
• Build analytics linking architecture decisions to downstream outcomes, including field issues, manufacturing escapes, and cost variance.
• Contribute to vehicle-level STPA, DFMEA, and fault analyses, and incorporate findings into the architecture and its models.
• Participate in architecture, interface, and safety design reviews across domains.
• Correlate models against real vehicle, laboratory rig, and supplier data.
• Document developed methods as playbooks that other engineers can run.

Benefits

• Competitive base salary.
• Potential eligibility for an annual company performance bonus program for full-time positions; payments are discretionary and not guaranteed.
• Eligibility for equity in the form of Restricted Stock Units (RSUs), subject to board approval and applicable plan terms and vesting requirements.
• Comprehensive benefits package for full-time employees, including health coverage, retirement savings, time off, and family planning programs; offerings vary by country.

What This Job Offers

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