Lead Cloud Automation Engineer (DevOps, AI/ML/Gen-AI)

We are looking for a skilled Lead Cloud Automation Engineer to strengthen our Automation Engineering team.

The role demands deep expertise in cloud infrastructure automation and DevOps, combined with solid knowledge in Infrastructure-as-Code (IaC) tools, generative AI, machine learning and AIOps. The successful candidate will be pivotal in enhancing our AIOps capabilities using generative AI models for anomaly detection, predictive maintenance and root cause analysis in a cloud environment.

Responsibilities
Design, develop and maintain automated workflows for cloud infrastructure using Terraform and other IaC tools
Enhance automation frameworks for infrastructure deployment across multiple cloud platforms
Develop, manage and integrate GenAI service catalog code generation models with cloud automation pipelines
Design and implement CI/CD pipelines to automate builds, testing and deployments
Write and maintain automation scripts using Python, Bash or similar languages
Design and develop generative AI models for AIOps applications using frameworks such as RAG with Langchain
Utilize Vector Document Sources and Vector Database Sources in the context of generative AI
Implement data streaming and manage cloud data lakes for AI model training
Integrate generative AI models with existing AIOps platforms to enhance operational efficiency
Collaborate with cross-functional teams to optimize cloud automation processes
Research and implement new automation tools and techniques to improve efficiency
Requirements
Bachelor's or Master's degree in Computer Science, Engineering or a related field
8+ years of experience with IaC tools, including Terraform and CloudFormation
Proven experience deploying generative AI models like RAG and understanding transformers
Strong proficiency in Python and GenAI frameworks, such as RAG and Agentic Workflow
Ability to build and manage Vector Document Sources using systems like Opensearch or Amazon Kendra
Competency in creating Vector Database Sources with cloud or non-cloud databases
Skills in data preparation, labeling and feature engineering for AI models
Experience with cloud data lakes and vector databases for AI training
Ability to create and manage the agentic workflow using ReAct Pattern or other GenAI platforms
Expertise in developing CI/CD pipelines for a range of cloud automation cases
Nice to have
Familiarity with Cloud GenAI platforms like Bedrock Agents
Experience integrating multi-agent systems for data aggregation in agentic workflows
Knowledge of MLOps pipelines for deploying and monitoring AI models