DLA - Senior Engineer

Overview

Senior engineer on General Motors' Global Manufacturing Engineering team at GMTCI, building full-stack manufacturing data analytics and intelligence applications that apply big data analytics to GM manufacturing processes across global plants.

What you'll do

• Design, develop, and maintain full-stack manufacturing intelligence applications using modern frontend, backend, and database technologies
• Build intuitive React/TypeScript user experiences for manufacturing dashboards, workflow tools, operational insights, and engineering applications
• Develop scalable backend services and APIs using Python and FastAPI or comparable frameworks, with clear service boundaries, resilient error handling, and efficient request processing
• Integrate applications with manufacturing and enterprise systems, including MES, SCADA, PLC/controls data, historians, equipment interfaces, and event-driven data services
• Design and optimize PostgreSQL data models, queries, and data pipelines for production, quality, equipment, and process information
• Implement secure authentication, authorization, auditability, and data-access controls for applications used across GM manufacturing and engineering environments
• Deploy and operate applications across enterprise, cloud, and edge environments using Docker, Kubernetes, CI/CD automation, and production monitoring
• Create automated unit, integration, and end-to-end tests and establish engineering practices that improve application reliability, maintainability, and release quality
• Translate manufacturing and engineering problems into clear technical designs, user stories, acceptance criteria, and measurable product outcomes
• Collaborate with controls, manufacturing, quality, data science, cybersecurity, and IT teams to deliver solutions that improve visibility, productivity, quality, and decision-making
• Troubleshoot production issues, perform root-cause analysis, and implement performance and reliability improvements across the application stack
• Document architecture, APIs, deployment procedures, operating standards, and support processes while contributing to a culture of continuous improvement

What you'll need

• Bachelor's or higher degree in Computer Science, Software Engineering, Electrical Engineering, Computer Engineering, or equivalent experience
• Ability to work effectively in both central engineering and plant environments, including time on the plant floor around operating equipment
• 5+ years of professional software engineering experience building and supporting production full-stack applications
• 3+ years of experience delivering manufacturing intelligence, industrial software, or data-intensive enterprise applications across frontend, backend, and data layers
• Advanced TypeScript/JavaScript skills with React, including component architecture, state management, data visualization, responsive and accessible user interfaces, and frontend testing
• Strong Python development skills with FastAPI or comparable frameworks, including asynchronous programming, REST/OpenAPI service design, request validation, dependency management, and automated testing
• Advanced SQL and PostgreSQL skills, including relational data modeling, schema design, migrations, indexing, query and transaction performance, and data-quality controls
• Experience delivering manufacturing intelligence, industrial software, or data-intensive enterprise applications that connect operational data to business and engineering workflows
• Experience designing data pipelines and event-driven architectures for equipment telemetry, time-series data, production data, quality data, and manufacturing workflows
• Hands-on experience with Git, Docker, Kubernetes, CI/CD automation, environment configuration, and deployment practices for production applications
• Demonstrated intermediate-level proficiency with Microsoft Azure services and cloud-based application development
• Experience implementing automated unit, integration, contract, and end-to-end testing, as well as observability using structured logging, metrics, tracing, health checks, and alerting
• Working knowledge of application and platform security, including OAuth/OIDC, role-based access control, secrets management, secure coding, vulnerability remediation, and least-privilege design
• Demonstrated ability to troubleshoot distributed systems, diagnose performance and reliability issues, and translate manufacturing requirements into maintainable technical designs and production releases
• Basic understanding of Databricks and its integration with other systems
• Working understanding of automotive manufacturing processes
• Working knowledge of applying AI/ML techniques to manufacturing data, including integrating AI services and models into production applications, evaluating model outputs, using prompt engineering or retrieval-augmented generation (RAG), and monitoring AI system performance

Nice to have

• Intermediate-to-expert proficiency with Databricks, including Spark and SQL data pipelines, Delta Lake, workflow orchestration, data-quality controls, and integration with manufacturing and enterprise systems
• Experience integrating OT and IT systems such as MES, SCADA, PLC/controls systems, OPC UA, MQTT, REST APIs, historians, and event or message-based platforms
• Experience working with manufacturing data models, time-series data, equipment telemetry, production genealogy, quality data, or process data
• Experience building data visualization and analytical user experiences for operational, engineering, quality, or maintenance users
• Experience with cloud-native and edge architectures, including Kubernetes, infrastructure as code, distributed systems, and disconnected or intermittently connected environments
• Knowledge of GM's controls standards, manufacturing technology standards, or comparable industrial automation and software integration standards
• Experience with event-driven architectures, streaming platforms, message queues, data historians, or real-time data processing
• Experience implementing observability practices, including structured logging, metrics, distributed tracing, alerting, and service-level objectives
• Experience with automated security scanning, software supply-chain controls, vulnerability remediation, and cybersecurity practices for operational technology environments
• Experience leading technical design discussions, mentoring engineers, reviewing code, and establishing reusable software patterns across teams
• Strong collaborative skills and the ability to communicate effectively with technical and non-technical stakeholders in a fast-paced manufacturing environment

Details

• Location: Bengaluru, Karnataka, India
• Work arrangement: Hybrid, reporting to the office four times per week or other frequency dictated by the business
• Sponsorship: GM does not provide immigration-related sponsorship for this role
• Primarily a non-travel job; business travel only for special requirements and of short duration
• Possible International Short-Term assignment for 6 months in the first year for training and development, depending on need