Senior Software Engineer - Platform

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 Identify and implement AI and intelligent automation opportunities that improve efficiency, user experience, and business outcomes Develop agentic AI solutions that streamline business processes and enable practical, secure, and responsible use of AI Evaluate new tools and technologies through proofs of concept Mentor junior engineers and collaborate cross‑functionally to deliver scalable platform and integration solutions Your Skills & Abilities (Required Qualifications) 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 BrowserStack 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 #J-18808-Ljbffr General Motors