Staff Software Engineer

General Motors • Sunnyvale, CA

34d • Remote

About The Position

About the Role We are seeking an experienced Staff Software Engineer to lead the technical direction for the data collection and its ecosystem of integrations, automations, and end-to-end observability. Scaling data collection is key to enabling autonomous and eyes off driving. In this role, you will design and build the platform that ensures high-quality data flows from vehicles into our AI/ML and analytics stacks, with strong guarantees around data quality, traceability, and operational excellence. You will work closely with AI research engineering, data engineering, vehicle engineering, data science, data quality, product and operations teams to deliver robust, observable services and user experiences that scale across General Motors programs. What You’ll Do Own the system end-to-end – architecture, implementation, and operations for web UI, APIs, and backend services that power data collection and vehicle configuration workflows. Design and implement integrations between UX and core platforms (data warehouse/lake, streaming pipelines, vehicle telemetry, configuration management, API gateway, identity & access, taxonomy/metadata services). Build automations and orchestration for config rollout, data ingest, validation, and feedback loops (e.g., scheduled jobs, event-driven workflows, rule-based triggers). Establish end-to-end observability: metrics, logs, traces, and dashboards that cover data flows from vehicles endpoints to downstream consumers. Raise the bar on data quality and governance by defining and enforcing contracts, validation checks, and schemas across various systems. Define and evolve system architecture to meet GM’s standards for security, compliance, and reliability, including access control, auditability, and PII-safe data handling. Create and standardize APIs and event schemas that make an easy-to-integrate platform for other applications and services. Partner cross-functionally with: AI research team to assess data integrity and mining quality to ensure we collected right amount of data via the data collection platform. Data Engineering on ingestion, transformation, and storage patterns. Vehicle Engineering on in-vehicle integration and configuration lifecycles. Data Science & Analytics on data access patterns, features, and experimentation needs. Data Quality & Taxonomy teams on metrics, definitions, and consistent metadata. Define and track platform metrics (reliability, latency, throughput, data quality scores, correctness of deployments) and create a roadmap for scale, resilience, and faster development/deployment cycles. Drive the full project lifecycle – requirements, design docs, prototyping, implementation, code reviews, rollout, monitoring, and continuous improvement. Review and improve engineering practices – technical designs, code quality, documentation, and development processes across the team. Mentor and grow engineers, influence technical direction across adjacent teams, and participate in hiring. Your Skills & Abilities (Required Qualifications) Proven experience owning high-availability, mission-critical services in production, including on-call participation and incident response. Track record of leading large technical initiatives from concept to production and iterative evolution (e.g., new platform, major re-architecture, or multi-system integration). Ability to identify and decompose broad technical, functional, and business challenges into clear, executable initiatives across multiple teams. Experience designing enterprise, systems, and integration architectures (APIs, event-driven systems, data flows, security boundaries, contracts) and setting associated standards and frameworks. Strong programming experience in Python, Java, or Go (2+ of these preferred), including building backend services and APIs. Experience with cloud infrastructure (e.g., GCP/Azure/AWS), including: Infrastructure-as-code, automation, and configuration management. CI/CD pipelines, artifact management, feature flags, and rollout strategies. Experience building production-level frontend applications using React, Angular, or similar frameworks. Strong understanding of JavaScript/TypeScript and modern frontend fundamentals (state management, performance, accessibility, testing). Hands-on experience with observability tooling (metrics, logging, tracing, dashboards) and using telemetry to drive product and reliability decisions. Comfort working with data platforms (data warehouses/lakes, streaming systems, ETL/ELT) and designing robust interfaces to them. Expertise in integration, automation, and platform thinking – you enjoy making complex systems simpler, safer, and more reusable. BS, MS, or PhD in Computer Science, Engineering, Math, or related field, or equivalent practical experience.

Requirements

• Proven experience owning high-availability, mission-critical services in production, including on-call participation and incident response.
• Track record of leading large technical initiatives from concept to production and iterative evolution (e.g., new platform, major re-architecture, or multi-system integration).
• Ability to identify and decompose broad technical, functional, and business challenges into clear, executable initiatives across multiple teams.
• Experience designing enterprise, systems, and integration architectures (APIs, event-driven systems, data flows, security boundaries, contracts) and setting associated standards and frameworks.
• Strong programming experience in Python, Java, or Go (2+ of these preferred), including building backend services and APIs.
• Experience with cloud infrastructure (e.g., GCP/Azure/AWS), including: Infrastructure-as-code, automation, and configuration management. CI/CD pipelines, artifact management, feature flags, and rollout strategies.
• Experience building production-level frontend applications using React, Angular, or similar frameworks.
• Strong understanding of JavaScript/TypeScript and modern frontend fundamentals (state management, performance, accessibility, testing).
• Hands-on experience with observability tooling (metrics, logging, tracing, dashboards) and using telemetry to drive product and reliability decisions.
• Comfort working with data platforms (data warehouses/lakes, streaming systems, ETL/ELT) and designing robust interfaces to them.
• Expertise in integration, automation, and platform thinking – you enjoy making complex systems simpler, safer, and more reusable.
• BS, MS, or PhD in Computer Science, Engineering, Math, or related field, or equivalent practical experience.

Nice To Haves

• Experience with REST/JSON and GraphQL APIs, webhooks, and event-driven or streaming architectures (e.g., Kafka, Pub/Sub).
• Experience building internal tools and platforms that are core to engineers’ or operators’ daily workflows.
• Experience with data modeling, taxonomy, and metadata systems for analytics, ML, or large-scale data platforms.
• Familiarity with data quality frameworks (validation, contracts, lineage, anomaly detection) and tools.
• Experience with ML, experimentation, or data science workflows, especially around data collection and feature pipelines.
• Prior work on end-to-end observability initiatives (defining SLOs, setting up dashboards, alerts, and runbooks).
• Self-motivated, strong at execution, and oriented toward clear, measurable impact.
• Excellent communication skills to: Align and influence cross-functional stakeholders. Resolve conflicts and build consensus. Communicate trade-offs, risks, and technical decisions to both technical and non-technical audiences.

Responsibilities

• Own the system end-to-end – architecture, implementation, and operations for web UI, APIs, and backend services that power data collection and vehicle configuration workflows.
• Design and implement integrations between UX and core platforms (data warehouse/lake, streaming pipelines, vehicle telemetry, configuration management, API gateway, identity & access, taxonomy/metadata services).
• Build automations and orchestration for config rollout, data ingest, validation, and feedback loops (e.g., scheduled jobs, event-driven workflows, rule-based triggers).
• Establish end-to-end observability: metrics, logs, traces, and dashboards that cover data flows from vehicles endpoints to downstream consumers.
• Raise the bar on data quality and governance by defining and enforcing contracts, validation checks, and schemas across various systems.
• Define and evolve system architecture to meet GM’s standards for security, compliance, and reliability, including access control, auditability, and PII-safe data handling.
• Create and standardize APIs and event schemas that make an easy-to-integrate platform for other applications and services.
• Partner cross-functionally with: AI research team to assess data integrity and mining quality to ensure we collected right amount of data via the data collection platform. Data Engineering on ingestion, transformation, and storage patterns. Vehicle Engineering on in-vehicle integration and configuration lifecycles. Data Science & Analytics on data access patterns, features, and experimentation needs. Data Quality & Taxonomy teams on metrics, definitions, and consistent metadata.
• Define and track platform metrics (reliability, latency, throughput, data quality scores, correctness of deployments) and create a roadmap for scale, resilience, and faster development/deployment cycles.
• Drive the full project lifecycle – requirements, design docs, prototyping, implementation, code reviews, rollout, monitoring, and continuous improvement.
• Review and improve engineering practices – technical designs, code quality, documentation, and development processes across the team.
• Mentor and grow engineers, influence technical direction across adjacent teams, and participate in hiring.

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.
• 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.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Number of Employees: 5,001-10,000 employees