Senior Platform Engineer

EPAM Systems; Coimbatore District; On-site; INR 1,800,000 - 3,000,000; Full time

Job summary

EPAM Systems is seeking a Senior Platform Engineer to architect and build automated cloud infrastructure, embedding GenAI capabilities within AIOps platforms and driving cloud automation innovations.

You will lead DevOps and MLOps initiatives, design CI/CD pipelines, implement IaC with Terraform and CloudFormation, and craft scalable data pipelines and AI workflows across AWS, Google Cloud, and Azure.

Qualifications

• Bachelor's or Master's degree in Computer Science, Engineering, or a related discipline.
• Minimum 5 years in cloud infrastructure automation, scripting, and DevOps.
• Proficiency with IaC tools like Terraform, CloudFormation, or similar.
• Strong Python and cloud AI frameworks experience; design of generative AI workflows.

Responsibilities

• Develop automated workflows for provisioning cloud infrastructure using IaC tools such as Terraform.
• Create frameworks that support deployment, configuration, and management across various cloud environments.
• Manage and develop service catalog components and integrate with platforms like Backstage.
• Apply GenAI models to improve service catalog capabilities and automation pipelines.
• Architect and implement CI/CD pipelines for cloud automation.

Skills

DevOps

MLOps

Scripting

CI/CD

Education

Bachelor's or Master's in CS/Engineering

Tools

Terraform

CloudFormation

LangChain

Bedrock

Vertex AI

Azure AI

OpenSearch

Amazon Kendra

LangGraph

Job description

We're looking for a Senior Platform Engineer who can architect and build automated cloud infrastructure solutions, embed generative AI capabilities within AIOps platforms, and lead innovation efforts in cloud automation. This role calls for strong expertise in DevOps, MLOps, and observability tools to boost operational efficiency and improve service delivery.

Responsibilities

• Develop automated workflows for provisioning cloud infrastructure using IaC tools such as Terraform
• Create frameworks that support deployment, configuration, and management across various cloud environments
• Manage and develop service catalog components while ensuring smooth integration with platforms like Backstage
• Apply GenAI models to improve service catalog capabilities and elevate code quality within automation pipelines
• Architect and implement CI/CD pipelines, while maintaining CI pipeline code for cloud automation purposes
• Write automation scripts for cloud deployment orchestration using Python, Bash, or similar scripting languages
• Build and deploy generative AI models to support AIOps use cases like anomaly detection and predictive maintenance
• Leverage frameworks such as LangChain or cloud platforms including Bedrock, Vertex AI, and Azure AI to deploy RAG workflows
• Construct and fine-tune vector databases and document sources using tools such as OpenSearch, Amazon Kendra, or similar solutions
• Prepare and label datasets for generative AI models while maintaining scalability and data integrity
• Develop agentic workflows using frameworks like LangGraph or GenAI platforms such as Bedrock Agents
• Connect generative AI models with operational systems and AIOps platforms to strengthen automation
• Assess AI model performance and drive ongoing optimization efforts
• Build and maintain MLOps pipelines to track and address model decay
• Partner with cross-functional teams to foster innovation and enhance cloud automation workflows
• Investigate and propose new tools and best practices to strengthen operational efficiency

Requirements

• Bachelor's or Master's degree in Computer Science, Engineering, or a related discipline
• Minimum of 5 years working in cloud infrastructure automation, scripting, and DevOps
• Skilled in IaC tools including Terraform, CloudFormation, or comparable technologies
• Strong command of Python, cloud AI frameworks like LangChain, and generative AI workflow design
• Experience building and deploying AI models such as RAG or transformer-based architectures
• Skilled in constructing vector databases and document sources through tools like OpenSearch or Amazon Kendra
• Capable of preparing and labeling datasets for AI models while optimizing data inputs
• Familiar with cloud platforms such as AWS, Google Cloud, or Azure
• Able to implement MLOps pipelines and track AI system performance

Nice to have

• Familiarity with agentic architectures like React and techniques for flow engineering
• Experience using Bedrock Agents or LangGraph to build workflows
• Understanding of how to integrate generative AI into legacy or complex operational environments