Cloud Platform Engineer- AWS& Python

Job Responsibilities

· Design, build, and support cloud-native platforms and services running on AWS.

· Manage and enhance AWS-based sandbox, data engineering, and AI/ML development environments.

· Develop automation solutions, platform utilities, APIs, and operational tooling using Python.

· Provision, maintain, and optimize cloud infrastructure using Infrastructure as Code (Terraform).

· Develop, troubleshoot, and optimize Spark/PySpark workloads running on AWS EMR. 6. Support data processing, analytics, and AI/ML workloads at scale.

· Build and maintain CI/CD pipelines to streamline deployments and platform operations.

· Collaborate with data engineers, AI engineers, architects, and product teams to deliver scalable and reliable solutions.

· Monitor platform health, troubleshoot production issues, and drive operational excellence.

· Evaluate and implement emerging cloud, AI, and automation technologies.

· Ensure adherence to security, governance, reliability, and cloud engineering best practices.

Required Qualifications

· Bachelor’s degree in computer science, Computer Engineering, Information Technology, or equivalent experience.

· 5-8 years of experience in cloud platform engineering, software development, infrastructure automation, or related technical roles.

· Strong hands-on experience with AWS services, including: EC2 S3 IAM VPC RDS/Aurora EMR CloudWatch Lambda ECS/EKS

· Strong Linux administration experience, including scripting, troubleshooting, networking, system performance monitoring, and operational support.

· Advanced Python development skills for automation, API development, platform tooling, and data processing.

· Strong Infrastructure as Code experience using Terraform to provision and manage AWS environments.

· 7.Hands-on experience developing, troubleshooting, and optimizing Apache Spark and PySpark workloads.

· Experience provisioning, configuring, operating, and supporting AWS EMR clusters.

· Practical experience with AI/ML and Generative AI technologies, including: LLM-based applications AI Agents and Agentic Workflows MCP Servers and AI Tool Integrations Retrieval-Augmented Generation (RAG) Prompt Engineering and AI Automation Frameworks

· Experience with CI/CD tools such as Jenkins, GitHub, GitLab, Bitbucket, or similar platforms.

· Strong understanding of cloud security, access management, vulnerability remediation, and secure software development practices.

· Excellent analytical, problem-solving, troubleshooting, and communication skills.

Preferred Qualifications

· Experience with containerized platforms and orchestration technologies such as Docker, Kubernetes, and Amazon EKS.

· Experience designing and integrating REST APIs and microservices.

· Experience with monitoring, observability, and logging frameworks.

· Experience supporting JupyterHub, JupyterLab, or similar AI/ML and data science development environments.

· Familiarity with AI development tools such as GitHub Copilot, Amazon Q, Cursor, Claude Code, or equivalent AI-assisted engineering platforms.

· Experience building AI-enabled platforms, agentic workflows, or enterprise AI solutions.

· Knowledge of vector databases, embedding models, model gateways, and AI platform operations.

· AWS, Terraform, Kubernetes, or AI/ML certifications are a plus.