Cloud Software Engineer
Stefanini Group•Dearborn, MI
•Onsite
About The Position
Stefanini Group is hiring! Stefanini is looking for a Cloud Software Engineer, Dearborn, MI. We are seeking a Cloud Software Engineer who will support the development and deployment of a Telemetry & Observability Platform, integrating vehicle, diagnostic, engineering, manufacturing, and software data. Work with an Agile team to build cloud-native services, data integrations, user-facing features, and platform monitoring, while helping deliver scalable, cost-efficient cloud infrastructure for enterprise teams.
Requirements
- AWS, Google Cloud Platform (GCP), REST APIs, Java, JavaScript, SQL, Kubernetes, Docker, Apigee, Agile software development, Software Development Lifecycle (SDLC), GitHub, Spring Boot
- 2–5 years of software development experience
- Programming experience in one or more relevant languages, such as Python, Java, JavaScript, or TypeScript.
- Experience developing or consuming REST APIs and working with structured data formats such as JSON.
- Experience with relational databases, SQL, and basic data modeling.
- Experience using Git-based source control and participating in peer code reviews.
- Familiarity with automated unit and integration testing.
- Basic understanding of cloud computing, containerization, and CI/CD practices.
- Ability to diagnose software issues using application logs and debugging tools.
Nice To Haves
- Understanding of agentic AI workflows and data-pipeline development and processing.
- Familiarity with AI evaluation strategies using RAGAS, retrieval-augmented generation (RAG), vectorization, and LLM orchestration.
- Experience with Google Cloud Platform services such as Google Kubernetes Engine, Pub/Sub, Cloud Storage, or Cloud SQL.
- Experience with Docker, Kubernetes, Terraform, or similar cloud-native technologies.
- Experience developing frontend applications using React and TypeScript.
- Familiarity with event-driven architecture, asynchronous processing, and data pipelines.
- Experience implementing platform observability using logs, metrics, traces, dashboards, and alerting.
- Familiarity with OpenTelemetry or comparable observability standards and tooling.
- Experience with API specifications and tools such as OpenAPI or Swagger.
- Familiarity with authentication, authorization, role-based access control, and secure coding practices.
- Experience in integrating AI or machine-learning services through APIs.
- Familiarity with prompt management, AI response validation, confidence scoring, or human-feedback capture.
- Experience with telemetry, automotive diagnostics, connected-vehicle data, manufacturing information, or engineering lifecycle systems.
- General knowledge of diagnostic concepts such as DTCs, CAN, UDS, or DoIP is beneficial but not required.
- Experience working in an Agile or Scrum delivery model.
Responsibilities
- Build and integrate REST APIs, backend services, data-processing functions, and event-driven workflows.
- Develop integrations with approved vehicle, service, engineering, manufacturing, and software-factory data sources.
- Support ingestion, normalization, validation, storage, and retrieval of telemetry and diagnostic information.
- Contribute to web-based interfaces and dashboards that present diagnostic, operational, AI-performance, and platform-health information.
- Implement logging, metrics, distributed tracing, error handling, and health checks for platform services.
- Write unit, integration, API, and automated regression tests.
- Participate in code reviews and address feedback related to maintainability, performance, security, and coding standards.
- Support CI/CD pipelines, containerized deployments, configuration management, and cloud-environment troubleshooting.
- Assist with integrating AI services through governed APIs and standardized interface contracts.
- Implement role-based access controls and follow enterprise security, privacy, data-retention, and auditability requirements.
- Create and maintain technical documentation, including API specifications, deployment instructions, support procedures, and design notes.
- Participate in backlog refinement, estimation, sprint planning, demonstrations, and retrospectives.
- Investigate defects and operational issues using logs, metrics, traces, and other platform evidence.
- Identify technical risks, dependencies, and blockers, and communicate them promptly to the delivery team.
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
