Principal Systems Engineer – Autonomy Behavior Validation

General Motors

. Set the long-term technical strategy and systems engineering approach for autonomy behavior validation across capabilities, programs, and releases .

Posted 11/4/2026full-timeSunnyvale • California • United StatesSeniorLead💰 $238,700 - $365,700 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates deep expertise in autonomous driving systems, including perception, prediction, planning, and controls, while leading validation strategies and technical reviews. Proven ability to connect safety claims and requirements to evidence for high-consequence decisions in autonomous vehicle development.

Highest-signal resume keywords

Autonomous Driving ExpertiseSystems Engineering FundamentalsPython ProgrammingTechnical LeadershipValidation Strategy Design

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Behavior DecompositionMetrics DefinitionAcceptance Criteria DevelopmentSimulation EvaluationRisk QuantificationSafety Case DevelopmentValidation Software DesignHuman BenchmarkingFMEAISO 26262

Soft Skills

Clear CommunicationMentoring

Tools & Technologies

AI-Assisted WorkflowsData PipelinesScorecards

Industry Keywords

Autonomous VehiclesSafety-Critical ValidationDriverless LaunchRegulatory ComplianceV&V Planning

Tech Stack

Tools & technologies

Python

About the role

Key responsibilities & impact

Set the long-term technical strategy and systems engineering approach for autonomy behavior validation across capabilities, programs, and releases
Define behavior decomposition, metrics, acceptance criteria, coverage, confidence, and traceability
Connect safety claims, hazard analysis, and requirements to evidence for supervised release, driverless launch, and continuous release decisions
Present release 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
Lead efforts to close behavioral escapes and coverage gaps using fleet and incident data
Design validation strategies combining simulation, road data, closed-course testing, human references, and expert review
Make 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
Lead cross-functional technical reviews
Mentor engineers and improve systems engineering and validation across the AV organization

Requirements

What you’ll need

Master's degree in systems engineering, mechanical engineering, aerospace engineering, electrical engineering, computer science, robotics, or a related field
10 or more years of professional experience in autonomous vehicles, robotics, simulation, systems engineering, or safety-critical validation
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 across perception, prediction, planning, and controls
Deep systems engineering fundamentals, including decomposition, ODD definition, requirements strategy, V&V planning, and traceability
Experience leading simulation evaluation at scale
Strong Python and agentic workflow experience
Ability to design and review production-quality analysis and validation software
Demonstrated technical leadership across organizational boundaries
Experience explaining results, assumptions, and limitations clearly to engineers and senior leaders
Experience as a technical lead for validating a driverless commercial launch or expansion into new operating domains
Experience evaluating learned or end-to-end driving systems, including behavior, regressions, and generalization
Experience with human benchmarking and counterfactual or replay methods
Experience building or using a safety case
Familiarity with STPA, FMEA, fault trees, ISO 21448 (SOTIF), UL 4600, or ISO 26262
Experience with risk quantification and risk acceptance
Experience 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

Benefits

Comp & perks

Bonus potential through an incentive pay program based on company performance, job level, and individual performance
Medical insurance
Dental insurance
Vision insurance
Health Savings Account
Flexible Spending Accounts
Retirement savings plan
Sickness and accident benefits
Life insurance
Paid vacation and holidays
Tuition assistance programs
Employee assistance program
GM vehicle discounts