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

Lead Platform Engineer

The ideal candidate will have deep expertise in generative AI, machine learning, and AIOps, coupled with advanced knowledge of cloud infrastructure automation and modern engineering practices. This role involves leading the design, development, and implementation of transformative automation solutions using AI/ML and generative AI technologies.

Responsibilities

• Architect automated workflows for cloud infrastructure provisioning and management using IaC tools like Terraform
• Build and optimize automation frameworks to enable scalable multi-cloud infrastructure deployment and management
• Develop and enhance service catalog components with integration into platforms such as Backstage, leveraging GenAI models for code generation
• Implement CI/CD pipelines to streamline code builds, testing, and deployments, ensuring continuous delivery across diverse cloud environments
• Write and maintain automation scripts using Python, Bash, or similar scripting languages
• Act as deployment orchestrator, driving smooth, automated deployments across cloud ecosystems
• Design and implement generative AI models such as RAG and agentic workflows using frameworks like Langchain or platforms like Bedrock, Vertex, Azure AI
• Build and manage vector document sources and vector databases (e.g., Amazon Kendra, Opensearch) for AI-driven applications
• Prepare datasets, apply feature engineering, and optimize inputs for AI/ML models to enhance training and inference outcomes
• Create and integrate agentic workflows using approaches like ReAct patterns or Langraph engineering with cloud GenAI platforms
• Evaluate model performance and select appropriate large language models (LLMs) for specific use cases while preventing model decay through prompt/flow engineering
• Develop MLOps pipelines to deploy RAG or agentic flows, monitoring and iterating to ensure long-term operational performance
• Collaborate with cross-functional teams to develop innovative cloud automation and AIOps capabilities, driving operational efficiency

Requirements

• Bachelor's or Master's degree in Computer Science, Engineering, or a related technical field
• 7+ years of experience in cloud infrastructure automation, DevOps, and scripting
• Expertise in IaC tools such as Terraform, CloudFormation, or similar technologies
• Strong proficiency with Python and generative AI frameworks (RAG, agentic workflows)
• Proven experience working with GenAI platforms like Bedrock, Vertex AI, or Azure AI
• Competency in building and managing vector databases like Opensearch or Amazon Kendra
• Proficiency in data preparation, feature engineering, and dataset optimization for AI model development
• Background in designing and operating CI/CD pipelines and automating deployment workflows
• Knowledge of cloud automation tools, service catalogs, and integration platforms (e.g., Backstage)

Nice to have

• Familiarity with data streaming solutions and data lake architectures for real-time AI insights
• Understanding of ReAct patterns and Langraph engineering for agentic workflows
• Skills in integrating GenAI models into existing operational platforms for enhanced automation
• Showcase of experience driving AIOps initiatives in large-scale environments
• Flexibility to adapt and utilize emerging AI/ML technologies in solving complex operational challenges