Lead Platform Engineer

We are seeking an experienced Lead Platform Engineer to join our Automation Engineering team. The ideal candidate will excel in cloud infrastructure automation, generative AI, and machine learning, with a strong foundation in DevOps practices and modern scripting tools. This role involves designing cutting-edge AI-driven solutions for AIOps while innovating cloud automation processes to optimize operational efficiency. Responsibilities Design and develop automated workflows for cloud infrastructure provisioning using IaC tools like Terraform Build frameworks to support deployment, configuration, and management across diverse cloud environments Develop and manage service catalog components, ensuring integration with platforms like Backstage Implement GenAI models to enhance service catalog functionality and code quality across automation pipelines Design and implement CI/CD pipelines and maintain CI pipeline code for cloud automation use cases Write scripts to support cloud deployment orchestration using Python, Bash, or other scripting languages Design and deploy generative AI models for AIOps applications such as anomaly detection and predictive maintenance Work with frameworks like LangChain or cloud platforms such as Bedrock, Vertex AI, and Azure AI to deploy RAG workflows Build and optimize vector databases and document sources using tools like OpenSearch, Amazon Kendra, or equivalent solutions Prepare and label data for generative AI models, ensuring scalability and integrity Create agentic workflows using frameworks like Langraph or cloud GenAI platforms such as Bedrock Agents Integrate generative AI models with operational systems and AIOps platforms for enhanced automation Evaluate AI model performance and ensure continuous optimization over time Develop and maintain MLOps pipelines to monitor and mitigate model decay Collaborate with cross-functional teams to drive innovation and improve cloud automation processes Research and recommend new tools and best practices to enhance operational efficiency Requirements Bachelor's or Master's degree in Computer Science, Engineering, or a related field 7+ years of experience in cloud infrastructure automation, scripting, and DevOps Strong proficiency in IaC tools like Terraform, CloudFormation, or similar Expertise in Python, cloud AI frameworks such as LangChain, and generative AI workflows Demonstrated background in developing and deploying AI models such as RAG or transformers Proficiency in building vector databases and document sources using solutions like OpenSearch or Amazon Kendra Competency in preparing and labeling datasets for AI models and optimizing data inputs Familiarity with cloud platforms including AWS, Google Cloud, or Azure Capability to implement MLOps pipelines and monitor AI system performance Nice to have Knowledge of agentic architectures such as React and flow engineering techniques Background in using Bedrock Agents or Langraph for workflow creation Understanding of integrating generative AI into legacy or complex operational systems