Staff Automation & Platform Engineer

General Motors•Warren, MI

4d•$160,000 - $246,000•Remote

About The Position

Mission: Industrialize concepts into robust, production-grade platforms that the business can rely on. This is a flexible, full-stack Engineering role responsible for building and maintaining the software platform that connects AI models to business processes, as well as building agents directly within third-party platforms like Glean, Databricks, and Azure AI Foundry — while extending a software engineering mindset — testability, reliability, and maintainability — to agentic and automation systems, and helping other teams build to that same bar, so systems can be trusted to run in production without constant rework.

Requirements

Bachelor’s degree in Computer Science, Software Engineering, or related field.
8+ years of experience in Software Development, Automation Engineering, or Backend Engineering.
Strong proficiency across the stack — Frontend (ReactJS/Vite), Backend (Python), and Data (PostgreSQL/Databricks) — plus REST APIs and Workflow Orchestration tools.
Strong focus on code quality, error handling, and testing, applied equally to traditional software and to agentic/automation systems.
Demonstrated ability to rapidly learn and build production-quality agents and automations directly within third-party platforms such as Databricks, Glean, Azure AI Foundry, and Google tooling — not just custom code — to deliver solutions.

Nice To Haves

Familiarity with the VSSM business domain is a major advantage in prioritizing and shaping platform investments.
Ability to work on complex assignments requiring originality and ingenuity in approach.
Experience setting objectives that directly influence results and providing measurable contributions.
Resilience in approaching setbacks and comfort operating in fast-changing technical environments; ability to analyze failures and identify improvements.
Ability to work independently with broad latitude in decisions and actions in a complex environment.

Responsibilities

Platform Engineering: Build and maintain a full-stack software platform (frontend, backend, and data layers) that serves as the foundation for automation and AI-driven solutions across the business.
Production Hardening: Refactor prototypes into robust, production-grade code capable of handling high-volume transactions.
Engineering Rigor for Agentic Systems: Apply software engineering discipline — automated testing, error handling, observability, and reliability practices — to agentic frameworks and automation pipelines, not just traditional application code, so systems are durable and require minimal rework.
Advanced Logic Orchestration: Design complex workflows (such as agentic frameworks or LLM chaining) to solve intricate business problems.
System Integration: Manage API connections between predictive models, legacy systems, third-party platforms, and user interfaces.
Third-Party Platform Enablement: Continuously learn and build agents and automations directly within emerging third-party platforms (e.g., Databricks, Glean, Azure AI Foundry, Google), using them as core building blocks for new solutions and evaluating/adopting new tooling as the ecosystem evolves.
Resilience Engineering: Implement comprehensive logging, monitoring, and self-recovery mechanisms to minimize downtime.
Consulting & Best Practices: Document and evangelize engineering best practices and design patterns — including how to build high-quality, testable agents on platforms like Glean — and coach other teams so agents and automations they build independently meet the same reliability bar.
Advanced Support Escalation: Act as the technical escalation point for complex code-related issues after deployment.