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.