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

Lead Platform Engineer

The ideal candidate will have 7+ years of experience, combining deep proficiency in cloud automation, scripting, and Infrastructure-as-Code (IaC) tools with a strong background in AI/ML, especially generative AI and AIOps. Your contributions will drive innovations in AI-powered automation, enhance system efficiency, and deliver transformative solutions.

Responsibilities

• Design and maintain automated workflows for cloud infrastructure provisioning using IaC tools like Terraform and related technologies
• Develop robust automation frameworks for infrastructure deployment, configuration, and multi-cloud management
• Manage service catalog components integrated with platforms like Backstage for seamless cloud automation workflows
• Implement GenAI-based solutions, enabling automated service catalog creation and enhancing code quality across processes
• Build and optimize CI/CD pipelines to support comprehensive automation use cases across cloud environments
• Create and maintain scripts in Python, Bash, or other languages to support automation and deployment tasks
• Design genAI models such as RAG and Agentic Flows, leveraging frameworks like LangChain and platforms like Bedrock, Vertex AI, or Azure AI
• Construct vector databases and document sources using tools like Opensearch, Amazon Kendra, or equivalent technologies for AI training
• Prepare and label data, enabling optimized vector sources for AI/ML model applications
• Build agentic workflows using patterns like ReAct or cloud GenAI tools, integrating multiple operational systems effectively
• Design MLOps pipelines to deploy and maintain RAG and Agentic workflows, ensuring model performance through prompt engineering and vector source updates
• Collaborate with teams to integrate generative AI innovations into AIOps platforms, improving automation and system capabilities
• Research and recommend emerging technologies, tools, and practices to enhance infrastructure automation and AI workflow efficiency

Requirements

• Bachelor's or Master's degree in Computer Science, Engineering, or a related discipline
• 7+ years of experience in cloud automation, IaC tools like Terraform or CloudFormation, and multi-cloud platforms
• Expertise in Python for automation and AI/ML development
• Experience with generative AI frameworks, including RAG and Agentic Workflows, and their integration with tools like LangChain
• Familiarity with cloud platforms like AWS (Bedrock), Google Cloud (Vertex AI), or Microsoft Azure (Azure AI), along with associated automation tools
• Knowledge of data engineering, including data streaming, preparation, and labeling, with familiarity in cloud data lakes and vector databases
• Skills in building vector document sources using technologies like Opensearch, Amazon Kendra, or equivalent
• Proficiency in creating and optimizing CI/CD pipelines to support cloud-based automation

Nice to have

• Familiarity with state-of-the-art MLOps practices to ensure efficient AI/ML model deployment and monitoring
• Background in developing highly scalable workflows for predictive maintenance and anomaly detection using AI
• Understanding of advanced orchestration techniques for integrating AI/ML pipelines with AIOps platforms
• Capability to evaluate and adapt large language models (LLMs) for domain-specific use cases
• Showcase of innovative solutions that combine generative AI with operational insights for enhanced decision-making