Lead Platform Engineer (devops & Ai/ml/gen-ai)
- Epam Systems
- 8 - 12 years
- Chennai
- 3 months ago
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Job Description
We are seeking a highly skilled Lead Platform Engineer to join our Automation Engineering team and spearhead development efforts in cloud infrastructure automation, DevOps, and generative AI (Gen-AI).
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
Job Classification
Industry: IT Services & ConsultingFunctional Area / Department: Engineering - Software & QARole Category: Software DevelopmentRole: Search EngineerEmployement Type: Full timeContact Details:
Company: Epam SystemsLocation(s): Chennai
Keyskills: continuous integration ci/cd artificial intelligence cloud scripting coding automation cloud applications gcp devops iac tools ml cd python vmware microsoft azure aiml cloud platforms engineering aws cloudformation puppet as infrastructure terraform bash aws ci cd pipeline
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