Cloud Software Engineer

Stellantis Financial Services; Auburn Hills (MI); On-site; USD 140,000 - 180,000; Full time

Job summary

Stellantis Financial Services seeks a senior cloud engineer to design and operate cloud-native applications on AWS, build scalable backend systems, and drive CI/CD with infrastructure-as-code. The role focuses on Python/Java/Node.js, REST/GraphQL, Docker/Kubernetes, Terraform, DataDog/Grafana, and AI/ML integrations, with 5+ years’ production experience and strong AWS expertise.

You'll collaborate with platform, DevOps, data, QA, and business teams to deliver secure, reliable, and cost-efficient

Qualifications

• Bachelor’s degree or higher in a relevant field is required.
• 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/Node.js).
• Experience with containerized deployments (Docker + Kubernetes).
• Knowledge of security, scalability, and cloud cost optimization.

Responsibilities

• Design and operate production-grade AWS services.
• Collaborate with platform, DevOps, data, QA and business teams to deliver reliable cloud platforms.

Skills

AWS expertise

Cloud architecture

Backend programming

Education

Bachelor’s degree in Computer Science or related field

Master’s degree (preferred)

Tools

Python

Java

Node.js

Docker

Kubernetes

Terraform

CI/CD tooling

Job description

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.

Core Technical Stack:

Cloud & Infrastructure

• 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

Basic Qualifications:

• 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.

Preferred Qualifications:

• 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.

What Success Looks Like:

• Highly available, scalable AWS services deployed to production.

• Reduced operational overhead through automation and cloud-native solutions.

• Optimized infrastructure cost and improved system performance.

• Clean, maintainable, well-documented code with strong test coverage.

• Measurable business impact through reliable and efficient cloud platforms.