Top Engineering Jobs in Austin, TX

Leads software engineering teams delivering enterprise HRIS and corporate systems across cloud, SaaS, and hybrid environments. Responsibilities include setting technical priorities, guiding architecture, modernizing applications, developing APIs and platform capabilities, improving reliability and observability, and implementing Agile, DevSecOps, CI/CD, automation, and AI-enabled solutions. The manager also oversees hiring, performance management, stakeholder collaboration, responsible AI governance, cloud migrations to Azure, and engineering culture development.

Design, develop, and architect scalable Golang software supporting enterprise data architecture. Lead technical design, collaborate across teams, mentor engineers, solve complex technical problems, and contribute to Agile delivery practices. Ensure software quality through code reviews, automated testing, CI/CD, and operational support while shaping technical roadmaps and architectural direction.

Build and operate full-stack vehicle software integrity systems using Next.js and Go. Develop data visualizations and dashboards, extend shared component libraries, collaborate with product and design teams, and ensure code quality through testing, reviews, debugging, and performance analysis. The role requires technical ownership, architectural decision-making, cross-functional communication, mentoring, and effective delivery amid changing priorities.

Build and support authenticated owner web experiences across front-end React UIs and backend Java/Spring Boot services. Design, implement, test, and troubleshoot features and APIs, collaborate with product and design, contribute to architecture and CI/CD practices, and improve developer velocity and platform consistency.

Design and develop backend services, APIs, microservices, integrations, and event-driven solutions for digital commerce and order management. Own testing, CI/CD, deployments, observability, cloud infrastructure, and production reliability using Azure, Docker, and Kubernetes. Troubleshoot incidents, improve security and scalability, apply AI-assisted development practices, mentor engineers, participate in hiring, and communicate technical risks and decisions to stakeholders.

Designs and implements privacy-by-design controls across enterprise data platforms, analytics, AI systems, digital products, and connected vehicle technologies. Develops privacy-preserving solutions including pseudonymization, tokenization, encryption, masking, consent management, access controls, and data minimization. Partners with Engineering, Legal, Privacy, Cybersecurity, Product, and Data Governance teams to embed privacy requirements into software and vehicle development lifecycles. Supports standards, assessments, audits, control validation, remediation, and technical guidance.

Lead architecture and development of GM’s in-vehicle AI assistant platform on Android Automotive OS. Build scalable APIs, SDKs, edge-cloud integrations, CI and automated validation infrastructure, and robust AIDL/IPC application contracts. Guide engineering execution, optimize latency and memory, integrate AI/ML evaluation pipelines, and collaborate with product and UX teams. The role requires extensive Android architecture experience, technical leadership, Kotlin and Java expertise, and familiarity with distributed client-server systems.

Leads the architecture and development of scalable backend APIs, microservices, distributed systems, data pipelines, and integrations for vehicle commerce platforms. Responsibilities include modernizing legacy systems, implementing automation, writing secure and tested code, mentoring engineers, evaluating technologies, and championing CI/CD, observability, and performance improvements. The role requires expertise in Java, Spring Boot, Kafka, cloud-native infrastructure, Azure, containers, databases, and generative AI technologies.

Lead full-lifecycle software development integrating robots and plant-floor devices with manufacturing data systems. Build, maintain, debug, optimize, and secure production applications using C++, Java, Azure, ROS, testing, CI/CD, and agile practices. Collaborate with manufacturing, controls, OT/IT, and data teams; support on-call operations, resolve urgent production issues, mentor developers, and conduct code reviews.

Found and establish GM Vehicle Autonomy’s centralized SRE practice. Build shared reliability tooling, service catalogs, SLOs, error budgets, readiness automation, standards, and production infrastructure. Partner with service owners to assess criticality, dependencies, failure modes, and operational health. Improve incident response, post-incident practices, on-call sustainability, and toil reduction while driving adoption across infrastructure teams. The role requires strong software engineering and distributed-systems expertise across Linux, networking, Kubernetes, cloud, CI/CD, and observability.