Lead Platform Engineer

Lead Platform Engineer

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