Staff Automation & Platform Engineer

General Motors; Frankfort (KY); On-site; USD 120,000 - 180,000; Full time

Job summary

General Motors is seeking a seasoned full-stack Engineer to build and maintain a production-grade software platform that connects AI models to business processes. You will implement agentic workflows, integrate predictive models with legacy systems, and extend tooling within Databricks, Glean, and Azure AI Foundry to enable robust automation at scale.

The role emphasizes engineering rigor, testing, observability, and reliability across frontend, backend, and data layers, with a focus on

Qualifications

• Bachelor’s degree in CS, Software Eng or related field.
• 8 years of experience in Software Development, Automation Eng, or Backend Eng.
• Strong frontend (ReactJS/Vite) and backend (Python) proficiency, plus data (PostgreSQL/Databricks) and REST APIs.

Responsibilities

• Platform Engineering: Build and maintain a full-stack software platform for automation and AI-driven solutions.
• Production Hardening: Refactor prototypes into robust, production-grade code.

Skills

Frontend ReactJS

Backend Python

Data PostgreSQL/Databricks

REST APIs

Workflow Orchestration

Education

Bachelor’s degree in Computer Science, Software Engineering, or related field

Tools

Databricks

Glean

Azure AI Foundry

Google

Job description

Job Description

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.

Key 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.

Required Qualifications:

· Education: Bachelor’s degree in Computer Science, Software Engineering, or related field.

· Experience: 8 years of experience in Software Development, Automation Engineering, or Backend Engineering.

· Full-Stack Technical Depth: Strong proficiency across the stack — Frontend (ReactJS/Vite), Backend (Python), and Data (PostgreSQL/Databricks) — plus REST APIs and Workflow Orchestration tools.

· Engineering Rigor: Strong focus on code quality, error handling, and testing, applied equally to traditional software and to agentic/automation systems.

· Platform & Tooling