Senior Software Engineer - Platform at General Motors — Austin, USA | Base Career

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The Role

General Motors is seeking a Senior Software Engineer to support, design, and improve delivery of enterprise applications, integrations, and intelligent platform capabilities across the Global Physical Security and Medical portfolio.

This role focuses on modernizing mission-critical solutions across on-prem, cloud, SaaS, and hybrid environments, strengthening system reliability, enabling scalable integrations, and driving technical execution across a complex operational landscape.

The Senior Software Engineer will also help introduce AI-enabled capabilities in practical, secure, and responsible ways, supporting automation, advanced insights, and intelligent workflows that improve both service delivery and business decision-making.

What You'Ll Do

Build, maintain, and support COTS applications on Unix and Windows platforms that are essential to business operations

Deploy applications and infrastructure as code using Terraform and similar tools

Lead and support application migrations to SaaS and cloud-based platforms

Create, maintain, and improve automation and operational scripts for deployments, backups, monitoring, rollbacks, and routine maintenance

Build and support CI/CD pipelines across applications, integrations, and platform services

Monitor platform health and data pipelines, including alerting, capacity planning, performance tuning, and operational readiness

Plan and execute backups, disaster recovery testing, and restore procedures for supported applications

Enforce security best practices including secrets management, RBAC, patching, vulnerability remediation, SSO/SAML, and audit logging

Troubleshoot incidents across the application and integration stack, perform root cause analysis, and produce post-incident documentation

Maintain runbooks, playbooks, technical documentation, and regular housekeeping procedures

Drive improvements in system reliability, maintainability, observability, and supportability

Apply modern engineering practices including Agile, DevSecOps, CI/CD, automated testing, and release governance

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

5+ years of professional software engineering, systems engineering, or platform support experience

Strong experience with scripting and automation using Bash, Python, Java or similar languages

Hands-on experience with Terraform, GitHub, Linux, Windows Server, and SSO/SAML

Experience with cloud platforms such as AWS and/or Azure

Experience building and supporting CI/CD pipelines, deployment automation, testing strategies, and environment promotion

Experience with Databricks Asset Bundles, GitHub Actions, or similar modern delivery tooling

Experience deploying and supporting containerized applications using Docker, Kubernetes, or similar technologies

Experience with SQL and NoSQL databases such as PostgreSQL, MongoDB, and Redis

Strong Linux administration and networking fundamentals

Solid understanding of security practices including RBAC, secrets management, TLS, patching, and audit controls

Demonstrated ability to evaluate, design, and implement deployment architectures for complex data and application platforms

Excellent troubleshooting, communication, and documentation skills

What Will Give You A Competitive Edge (Preferred Qualifications):

Experience with OTEL, DataDog, and modern observability practices

Practical experience with tools such as Databricks Genie, Glean, Cursor, GitHub Copilot, or similar AI-enabled engineering tools

Familiarity with MCP-style integrations and AI tools that connect to enterprise systems and services

Experience applying AI and LLM capabilities to operational workflows, analytics, and decision support

Ability to uncover patterns and insights in structured and semi-structured data and translate them into business actions

Experience building real-time alerts, operational signals, predictive indicators, or intelligent automation workflows

Strong ability to frame AI-assisted analytical problems, evaluate model output quality, and apply responsible AI practices across governance, security, privacy, and quality

#LI-SB3

Senior Software Engineer - Platform

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