Principle Systems Engineer - Autonomy Behavior Validation

General Motors LLC; Sunnyvale (CA); On-site; USD 239,000 - 366,000; Full time

Job summary

General Motors seeks a Principal Autonomy Behavior Systems Engineer to define, evaluate, and release autonomous vehicle behaviors across the validation lifecycle. You will align safety claims with evidence and drive the autonomous behavior validation strategy through simulation, road data, and fleet insights.

The role requires deep expertise in perception, prediction, planning, and controls, with strong Python skills and a track record of leading cross‑functional reviews and engineering teams

Qualifications

• Master's degree in a relevant engineering field and 10+ years in autonomous vehicles, robotics, or safety‑critical validation.
• Proven record evaluating autonomous vehicles for a self‑driving fleet or high‑consequence product decisions.
• Deep, end‑to‑end knowledge of perception, prediction, planning, and controls in autonomous driving.
• Strong Python skills and experience with agentic workflows and validation software.

Responsibilities

• Set long‑term strategy and systems engineering approach for autonomy behavior validation across programs and releases.
• Define what 'ready' means for autonomous behavior and connect safety claims to evidence.
• Lead cross‑functional reviews and mentor engineers to raise validation standards.
• Diagnose issues across perception, prediction, planning, and controls and close gaps using fleet data.
• Design validation strategies combining simulation, road data, and human references.
• Guide tools, data pipelines, scorecards, and workflows toward scalable products.

Skills

Autonomy behavior validation

Python programming

Systems engineering

Leadership

Education

Master's degree in engineering

Tools

Simulation tools

Job description

Job Description The Role

As a Principal Autonomy Behavior Systems Engineer, you will be the technical authority for how GM's autonomous vehicle behavior is defined, evaluated, and judged ready for release. Your scope covers the full range of driving behaviors, from routine maneuvers to rare, safety‑critical events. It also covers the whole validation lifecycle, from product requirements through launch and continuous monitoring in the fleet. You will bring broad, deep expertise in autonomous driving. You know how the autonomy stack produces behavior, where it fails, and what evidence a behavior needs before it is ready for a self‑driving fleet. You will work across Behavior, Software, Simulation, Safety, Legal, Product, and Operations to build a validation system that supports sound safety and launch decisions and earns the trust of the engineers and leaders who depend on it.

What You'll Do

• Set the long‑term technical strategy and systems engineering approach for autonomy behavior validation across capabilities, programs, and releases. This includes behavior decomposition, metrics, acceptance criteria, coverage, confidence, and traceability.


• Define what "ready" means for autonomous behavior.


• Connect safety claims, hazard analysis, and requirements to the evidence behind supervised release, driverless launch, and continuous release decisions, and present those recommendations to senior leadership.


• Act as the organization's go‑to expert on autonomous driving behavior.


• Diagnose complex issues across perception, prediction, planning, and controls, and lead the work to close behavioral escapes and coverage gaps using fleet and incident data.


• Design validation strategies that combines simulation, road data, closed‑course testing, human references, and expert review.


• Make deliberate trade‑offs among coverage, confidence, fidelity, runtime, and cost.


• Guide validation tools, data pipelines, scorecards, and AI‑assisted or agentic workflows toward repeatable, scalable products used by many teams.


• Lead cross‑functional technical reviews, mentor engineers, and raise the bar for systems engineering and validation across the AV organization.

Required Qualifications

Master's degree in systems engineering, mechanical engineering, aerospace engineering, electrical engineering, computer science, robotics, or a related field, and 10 or more years of professional experience in autonomous vehicles, robotics, simulation, systems engineering, or safety‑critical validation.

• A proven record of evaluating autonomous vehicles for a self‑driving fleet, launch, supervised release, or other high‑consequence product decision, including owning or materially shaping the go/no‑go recommendation.


• Deep, end‑to‑end expertise in autonomous driving: how each part of the stack (perception, prediction, planning, and controls) shows up as on‑road behavior across a wide range of scenarios, road users, and operating conditions.


• Deep systems engineering fundamentals, including decomposition, ODD definition, requirements strategy, V&V planning, and traceability, plus experience leading simulation evaluation at scale.


• Strong Python and agentic workflow experience.


• You are comfortable designing and reviewing production‑quality analysis and validation software and using code to investigate an engineering question quickly.


• Demonstrated technical leadership across organizational boundaries, including setting direction adopted beyond a single team and explaining results, assumptions, and limitations clearly to engineers and senior leaders.

What Will Give You a Competitive Edge

• Experience as a technical lead for validating a driverless commercial launch or an expansion into new operating domains.


• Experience evaluating learned or end‑to‑end driving systems, including how to characterize their behavior, regressions, and generalization.


• Experience with human benchmarking (such as attentive‑human benchmarks) and counterfactual or replay methods, and how they fit within a broader validation strategy.


• Experience building or using a safety case, and familiarity with hazard analysis methods (STPA, FMEA, fault trees) and standards such as ISO 21448 (SOTIF), UL 4600, or ISO 26262.


• Experience with risk quantification and risk acceptance, and with turning legal or regulatory expectations into a defensible compliance strategy.


• Experience designing validation lifecycles, scorecards, confidence rubrics, or behavior protocols used by many engineering teams.

Compensation:

Salary range for this role: $238,700 to $365,700.

Bonus Potential: An incentive pay program offers payouts based on company performance, job level, and individual performance.

Benefits: GM offers a variety of health and wellbeing benefit programs. Benefit options include medical, dental, vision, Health Savings Account, Flexible Spending Accounts, retirement savings plan, sickness and accident benefits, life insurance, paid vacation & holidays, tuition assistance programs, employee assistance program, GM vehicle discounts and more.

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