Cloud Software Engineer

Cloud-Native Application DeveloperDesign 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 StackCloud & Infrastructure:AWS (EC2, S3, Lambda, API Gateway, IAM, CloudWatch, SNS/SQS, DynamoDB, RDS)Containerization: DockerOrchestration: EKS/ECS/FargateInfrastructure as Code: Terraform / CloudFormationCI/CD: GitHub Actions, GitLab CI, Jenkins, CodePipelineObservability: CloudWatch, DataDog, GrafanaBackend Development:Python (FastAPI, Flask) or Java/Node.jsREST / GraphQL API designMicroservices architectureEvent-driven systemsCaching strategies (Redis, ElastiCache)Data & Messaging:PostgreSQL, MySQL, DynamoDBElasticsearch / OpenSearchKafka / SNS / SQSData pipelines (Airflow or equivalent)AI/ML (Nice Leverage, Not Primary):AWS Bedrock or SageMaker integrationRAG-based services or LLM API integrationModel API orchestration and monitoringBasic QualificationsBachelor's degree in Computer Science, Computer Engineering, Electrical Engineering, or a related fieldA 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 QualificationsMaster's degree in Computer Science, Computer Engineering, Electrical Engineering, or a related fieldExperience 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 LikeHighly 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.