Senior Software Developer

Job Description

Vacancy Status:

Yes - This posting is for an existing vacancy within the organization and is open to new applications. (Backfill)

AI Disclosure:

As part of the application process, Artificial Intelligence will be used in the hiring process for this role

Hybrid - This role is categorized as hybrid. This means the successful candidate is expected to report to our hub in Markham, ON three times per week, at minimum.

Role overview

General Motors is seeking a Senior Software Developer to build and evolve the software platforms that support production mapping, Data Over the Air (DOTA) Back Office capabilities, and future map-database foundations.

This role is for a hands-on senior engineer who can design, implement, test, deploy, and operate reliable backend systems at production scale. The developer will contribute across REST services, distributed data workflows, cloud infrastructure, database architecture, release automation, observability, and operational support. The work will help deliver accurate map data and establish scalable foundations for future mapping and Super Cruise capabilities.

The ideal candidate combines strong software engineering fundamentals with practical experience building cloud-native services and data-intensive systems. Experience with mapping, geospatial data, ADAS, connected vehicles, OTA delivery, or other high-scale distributed platforms is valuable. Familiarity with emerging Agentic AI capabilities is a plus, but the primary focus is excellent software and platform engineering.

Key responsibilities

• Design and develop production-grade backend services and REST APIs that support DOTA Back Office workflows, map-data delivery, release management, and related Production Mapping capabilities.
• Build reliable services and data pipelines that ingest, transform, validate, store, version, archive, and distribute map data and metadata.
• Help define the next generation of map-database foundations, including data models, schemas, interfaces, data lifecycle strategies, partitioning, indexing, query performance, and evolution of database platforms over time.
• Develop software across the full SDLC: requirements clarification, design, implementation, code review, automated testing, deployment, monitoring, incident response, and continuous improvement.
• Apply sound software design principles, including modularity, maintainability, security, testability, resilience, observability, and clear separation of concerns.
• Deploy and operate workloads in approved cloud environments using modern cloud-native patterns, containerization, infrastructure as code, and automated CI/CD.
• Improve the reliability, scalability, performance, cost efficiency, and operational readiness of DOTA and map-data services.
• Build automated validation and release-readiness checks that help ensure map-data quality and safe, repeatable production releases.
• Collaborate with mapping, DOTA, data engineering, vehicle software, validation, infrastructure, and product stakeholders to translate business and technical needs into durable solutions.
• Participate in production support and contribute to operational practices such as dashboards, alerting, runbooks, root-cause analysis, and incident prevention.
• Mentor engineers through design reviews, code reviews, technical guidance, and knowledge sharing.
• Stay current with practical uses of AI-assisted development and Agentic AI, and identify appropriate opportunities to improve engineering productivity, diagnostics, testing, documentation, or operational workflows.
  
  
  

Required Qualifications

• Bachelor’s degree in Computer Science, Computer Engineering, Software Engineering, or a related technical discipline; equivalent practical experience may be considered.
• 5+ years of professional software engineering experience developing and supporting production systems.
• Strong proficiency in at least one backend programming language such as Python, Java, Go, C++, or C#.
• Demonstrated experience designing and implementing RESTful services, APIs, and backend applications.
• Strong database experience, including relational database design, SQL, schema design, data modeling, indexing, query optimization, transactions, and data integrity.
• Experience with one or more NoSQL, distributed, analytical, or cloud-native data technologies.
• Experience with software development fundamentals, object-oriented or equivalent design, algorithms and data structures, concurrency, error handling, and performance tradeoffs.
• Experience working through the SDLC, including requirements, architecture/design, implementation, unit and integration testing, code reviews, CI/CD, deployment, and production support.
• Experience developing cloud-based applications using services for compute, storage, networking, security, and monitoring.
• Experience with Git-based development workflows and automated build, test, and deployment pipelines.
• Strong communication and collaboration skills, with the ability to explain technical decisions to both engineering and non-engineering partners.
  
  
  

Preferred Qualifications

• Experience with Azure and/or Google Cloud Platform.
• Experience with Kubernetes, Docker, Terraform, Databricks, Apache Spark/PySpark, workflow orchestration, or event-driven systems.
• Experience with data-intensive systems, large-scale pipelines, data archiving and retrieval, data lineage, or high-volume content delivery.
• Experience with geospatial data, map databases, HD mapping, ADAS, autonomous vehicles, connected vehicles, OTA systems, or embedded/vehicle software platforms.
• Experience designing systems for high availability, horizontal scalability, disaster recovery, and operational resilience.
• Experience with observability practices, including structured logging, metrics, tracing, dashboards, alerting, and SLO-oriented operations.
• Familiarity with modern AI-assisted software development and Agentic AI concepts, such as LLM-enabled developer tools, workflow orchestration, retrieval-augmented systems, automated triage, or human-in-the-loop engineering workflows.
• Experience evaluating AI-enabled engineering workflows for accuracy, security, privacy, reliability, and responsible adoption.
  
  
  

Compensation: