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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Cloud Software Engineer - **Company:** Stellantis - **Location:** Auburn Hills, MI, United States - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Java (Programming Language), Application Programming Interfaces (APIs), Artificial Intelligence, Airflow, Amazon Web Services, Amazon Elastic Compute Cloud, Amazon S3, Automation of Tests, Big Data, Cloud Computing, Cloud Computing Security, Computer Engineering, Continuous Integration, DevOps, Distributed Systems, Amazon DynamoDB, Elasticsearch, Github, Identity and Access Management, Python (Programming Language), PostgreSQL, MySQL, Node.Js, Performance Tuning, Redis, Cloud Services, Azure Machine Learning, Amazon Simple Notification Service (SNS), Software Engineering, Data Streaming, Datadog, Data Logging, Spring Cloud, Amazon ElastiCache, Flask (Web Framework), Delivery Pipeline, Large Language Models, Grafana, Caching, Backend, Cloudformation, Fastapi, Event Driven Architecture, Amazon Relational Database Service, Containerization, Gitlab-ci, Kubernetes, Infrastructure Automation Frameworks, Information Technology, Low Latency, AWS Fargate, Apache Kafka, Graphql, Functional Programming, Api Design, Cloudwatch, Api Gateway, Restful APIs, Amazon Simple Queue Service (SQS), Data Pipelines, Docker, Jenkins, Databricks, Microservices - **Published:** August 7, 2026 - **Apply:** https://careers.stellantis.com/job/23675514/cloud-software-engineer-auburn-hills-mi/ ## About the Role * Bachelor's degree in Computer Science, Computer Engineering, Electrical Engineering, or a related field * A minimum of 5 years of software development experience in production environments. * Strong hands-on experience with AWS cloud services. * Experience designing and operating distributed systems. * Proficiency in at least one backend language (Python, Java, or Node.js). * Experience with containerized deployments (Docker + Kubernetes/ECS/EKS). * Strong understanding of system design, scalability, and cloud security best practices. * Experience with CI/CD, automated testing, and infrastructure automation., * Master's degree in Computer Science, Computer Engineering, Electrical Engineering, or a related field * Experience integrating AI/ML services into production systems. * Experience with Databricks or large-scale data processing. * Familiarity with automotive systems or enterprise PLM environments. * Knowledge of event streaming architectures and high-throughput systems. * Experience in cost optimization for cloud workloads. ## Description QuantitativeValue 1000000.0 1.0 YEAR 2026-08-06 What we do: * Design and develop cloud-native applications and microservices on AWS. * Build scalable, highly available backend systems using modern architecture patterns. * Develop and maintain RESTful/GraphQL APIs and event-driven services. * Architect distributed systems with focus on reliability, security, scalability, and cost optimization. * Implement CI/CD pipelines, infrastructure-as-code, and automated testing. * Build observability frameworks including logging, monitoring, and alerting. * Optimize system performance, latency, throughput, and resource utilization. * Integrate AI/ML or GenAI services (e.g., AWS Bedrock) where applicable to enhance automation or analytics. * Collaborate with cross-functional teams including platform, DevOps, data, QA, and business stakeholders., * AWS (EC2, S3, Lambda, API Gateway, IAM, CloudWatch, SNS/SQS, DynamoDB, RDS) * Containerization: Docker * Orchestration: EKS/ECS/Fargate * Infrastructure as Code: Terraform / CloudFormation * CI/CD: GitHub Actions, GitLab CI, Jenkins, CodePipeline * Observability: CloudWatch, DataDog, Grafana Backend Development * Python (FastAPI, Flask) or Java/Node.js * REST / GraphQL API design * Microservices architecture * Event-driven systems * Caching strategies (Redis, ElastiCache) Data & Messaging * PostgreSQL, MySQL, DynamoDB * Elasticsearch / OpenSearch * Kafka / SNS / SQS * Data pipelines (Airflow or equivalent) AI/ML (Nice Leverage, Not Primary) * AWS Bedrock or SageMaker integration * RAG-based services or LLM API integration * Model API orchestration and monitoring ## Related Videos - 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