Platform Engineer (DevOps & AI/ML/Gen-AI)

Office in Hyderabad, Bangalore, Pune, Gurgaon

Platform Engineering

We are seeking a skilled Platform Engineer to join our Automation Engineering team, bringing expertise in cloud infrastructure automation, DevOps, scripting, and advanced AI/ML practices.

The role focuses on integrating generative AI into automation workflows, enhancing operational efficiency, and supporting cloud-first initiatives.

Responsibilities

Design cloud automation workflows using Infrastructure-as-Code tools such as Terraform or CloudFormation
Build scalable frameworks to manage infrastructure provisioning, deployment, and configuration across multiple cloud platforms
Create service catalog components compatible with automation platforms like Backstage
Integrate generative AI models to improve service catalog functionalities, including automated code generation and validation
Architect CI/CD pipelines for automated build, test, and deployment processes
Maintain deployment automation scripts utilizing technologies such as Python or Bash
Implement generative AI models (e.g., RAG, agent-based workflows) for AIOps use cases like anomaly detection and root cause analysis
Employ AI/ML tools such as LangChain, Bedrock, Vertex AI, or Azure AI for advanced generative AI solutions
Develop vector databases and document sources using services like Amazon Kendra, OpenSearch, or custom solutions
Engineer data pipelines to stream real-time operational insights that support AI-driven automation
Build MLOps pipelines to deploy and monitor generative AI models, ensuring optimal performance and avoiding model decay
Select appropriate LLM models for specific AIOps use cases and integrate them effectively into workflows
Collaborate with cross-functional teams to design and refine automation and AI-driven processes
Research emerging tools and technologies to enhance operational efficiency and scalability

Requirements

Bachelor's or Master's degree in Computer Science, Engineering, or related field
3-8 years of experience in cloud infrastructure automation, DevOps, and scripting
Proficiency with Infrastructure-as-Code tools such as Terraform or CloudFormation
Expertise in Python and generative AI frameworks like RAG and agent-based workflows
Knowledge of cloud-based AI services, including Bedrock, Vertex AI, or Azure AI
Familiarity with vector databases like Amazon Kendra, OpenSearch, or custom database solutions
Competency in data engineering tasks such as feature engineering, labeling, and real-time data streaming
Proven track record in creating and maintaining MLOps pipelines for AI/ML models in production environments

Nice to have

Background in Flow Engineering tools such as Langraph or platform-specific workflow orchestration tools
Understanding of comprehensive AIOps processes to refine cloud-based automation solutions