Role Overview:
We are seeking a Lead Infrastructure Automation & GenAI Engineer with 8 to 12 years of experience to bridge the gap between traditional enterprise IT infrastructure and cutting-edge artificial intelligence. In this role, you will lead the architecture and development of automated storage workflows while hands-on building and maintaining enterprise-grade Generative AI and Retrieval-Augmented Generation (RAG) pipelines. You will oversee engineering teams, define coding standards, and build intelligent self-service systems that optimize IT operations.
Core Responsibilities
- AI & RAG Development: Design, build, and optimize production-level RAG pipelines, integrating Large Language Models (LLMs), semantic vector embeddings, and backend frameworks to automate IT incident resolutions.
- Infrastructure Automation: Lead end-to-end storage provisioning and automation workflows across enterprise systems like Dell EMC PMAX and Huawei OceanStor/Dorado.
- Backend & UI Engineering: Architect high-performance, asynchronous REST APIs using Python FastAPI and develop intuitive user interfaces using Streamlit.
- Team Leadership: Mentor and guide engineering teams, establish Git-based version control practices, and drive delivery sprints using Agile/Kanban methodologies.
- Legacy Monitoring Integration: Leverage deep expertise in event correlation architectures (IBM Tivoli Netcool, VMware/Dell Smarts) to design automated ticketing and self-healing system integrations with ServiceNow and BMC Remedy.
Required Technical Skills
- AI/GenAI: RAG Pipelines, LangChain, Milvus DB, ChromaDB, Semantic Search
- Development: Python, FastAPI, Streamlit, Perl, Shell Scripting, REST APIs
- Enterprise Infrastructure: Dell EMC PMAX, Huawei OceanStor, SAN/NAS, IBM Tivoli Netcool (Omnibus, Impact), VMware Smarts
- Databases & Tools: Oracle, SQL, Sybase, Git, Jira, CI/CD
Email resume to: Anuradha.ang@gmail.com
