Cloud Software Engineer

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.
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