AI/ML Ops Lead

Location: Hyderabad, Telangana, India

Employment Type: Full time

Work Mode: Hybrid

Experience: 7+ Years

About the role :

We are seeking an experienced AI/ML Ops Lead to drive the successful transition, deployment, and operational support of enterprise AI/ML applications. The role focuses on ensuring production readiness, stability, scalability, and performance of AI solutions, including GenAI, LLMs, RAG, and Agentic AI applications.

You will collaborate with Development, Architecture, DevOps, and Operations teams to support deployments, resolve complex production issues, and enhance operational efficiency through automation and continuous improvement.

Key Responsibilities:

- Lead the AI/ML application transition from Development/Delivery to Operations, ensuring production readiness and smooth handover.
- Provide technical leadership for GenAI, ML, LLM, RAG, Agentic AI, and AI-enabled applications across deployment, stabilization, and ongoing Operations.
- Work closely with Development, AI Architects, DevOps, Infrastructure, QA, L2/L3 Support, and Business teams to ensure successful application transition and operational readiness.
- Assess application readiness across models, data pipelines, APIs, integrations, dependencies, deployment, monitoring, security, and performance before production transition.
- Lead technical activities for AI/ML application deployments, releases, upgrades, enhancements,



migrations, and production changes.
- Drive effective knowledge transfer and operational handover, ensuring support teams have the required technical documentation, runbooks, troubleshooting procedures, and application knowledge.
- Provide technical leadership to L2/L3 support teams for complex AI/ML production incidents, troubleshooting, root cause analysis, and application stabilization.
- Monitor and optimize AI/ML application performance, model behavior, availability, scalability, reliability, and resource utilization in production.
- Collaborate with DevOps and Cloud teams on CI/CD, automation, containerization, cloud deployment, monitoring, logging, alerting, and observability.
- Support the AI Solution Architect in reviewing technical designs, Architecture Handbooks, IQ/OQ, ITOH, validation documents, and operational artifacts from an AI/ML perspective.
- Ensure AI/ML applications comply with security, privacy, governance, responsible AI, regulatory, and operational requirements.
- Identify technical and operational risks and drive mitigation, preventive actions, continuous improvement, automation, and operational efficiency across AI/ML applications.
- Act as the key AI/ML technical point of contact for Operations, supporting critical incidents, releases, transitions, and ongoing application stability.

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