Software Engineering Manager – Autonomous Vehicle Data

General Motors

. Lead the AV Data Processing and Services team .

Posted 10/22/2026full-timeUnited StatesSeniorLeadWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in building and optimizing petabyte-scale distributed data pipelines and storage systems, with a strong focus on cloud infrastructure and engineering leadership. Proven ability to mentor teams and translate complex requirements into actionable technical roadmaps.

Highest-signal resume keywords

Petabyte-Scale Data PipelinesCloud Infrastructure OptimizationC++, Rust, Go, Python ProficiencyApache Spark, Beam, Kafka ExperienceEngineering Leadership

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Distributed SystemsBig Data PlatformsBatch Inference ProcessingStreaming ServicesData LineageAutomated TestingIncident ManagementRoot-Cause AnalysisData-Intensive ArchitecturesObservability

Soft Skills

MentoringTeam LeadershipCross-Functional Collaboration

Tools & Technologies

AWSAzureGCPS3Apache FlinkApache BeamKafkaIcebergDelta LakePresto/Trino

Industry Keywords

Autonomous Vehicle TechnologySelf-Driving TechnologyTechnical DesignCloud ComputeProduction-Grade SLAs

Tech Stack

Tools & technologies

ApacheAWSAzureCloudDistributed SystemsGoogle Cloud PlatformKafkaPythonRayRustSparkC++Go

About the role

Key responsibilities & impact

Lead the AV Data Processing and Services team
Build core pipelines and storage backbones that transform and serve petabyte-scale autonomous vehicle telemetry
Power GM’s perception, planning, ML training, safety metrics, and simulation loops
Contribute directly to technical design, implementation, and delivery as a player-coach
Mentor and guide the broader engineering team
Recruit, mentor, and grow a high-performing team of software and data engineers
Own the vision and architectural roadmap for AV Data services
Develop batch inference processing tools and streaming services for replay and simulation tools
Optimize cloud compute and storage across AWS, Azure, and GCP, including S3 tiering and distributed caches
Establish production-grade SLAs, monitoring, data lineage, and automated testing
Own incident management and root-cause analysis for mission-critical platform outages

Requirements

What you’ll need

BA or BS in Computer Science, Electrical Engineering, Mathematics, Physics, or another relevant field; or equivalent real-world experience
8+ years of professional software engineering experience in distributed systems, big data platforms, or cloud infrastructure
2+ years in formal engineering leadership
Experience designing, operating, and scaling petabyte-scale distributed data pipelines and storage systems
Experience with Apache Spark, Beam, Ray, Flink, Kafka, Iceberg, Delta Lake, and/or Presto/Trino
Expert-level proficiency in C++, Rust, Go or Python
Experience deploying and managing services in at least one major public cloud provider: Azure, GCP or AWS
Experience utilizing automation and observability for operational excellence
Proven ability to translate complex, ambiguous cross-functional requirements into technical roadmaps and reliable software deliverables
Passion for self-driving technology
Comfortable delivering in a polyglot programming environment
Experience delivering data-intensive distributed compute architectures
Must not require GM immigration-related sponsorship now or in the future, including H-1B, OPT, STEM OPT, CPT, TN, J-1, or other immigration support

Benefits

Comp & perks

Hybrid work arrangement with expected reporting to a specific location at least 3 times a week
Relocation benefits available for candidates who qualify under company policy
GM benefits supporting employee well-being at work and at home
Inclusive workplace and reasonable accommodation support