Description

You will define and implement AI Ops, MLOps, and LLM Ops strategies for enterprise platforms, owning the end-to-end model lifecycle from deployment to optimization.

This role is on-site.

Responsibilities

• Manage end-to-end AI operations lifecycle, including deployment, monitoring, scaling, and optimization of production AI systems.
• Establish robust model monitoring, observability, and alerting frameworks to ensure high availability and reliability.
• Implement model lifecycle management processes such as versioning, retraining, rollback, and drift detection.
• Drive the adoption of CI/CD and DevSecOps practices specifically tailored for AI/ML systems.
• Optimize cost, latency, and resource utilization while ensuring governance, risk, and security compliance.

Required Skills

• Strong expertise in AI Ops, MLOps, and LLM Ops practices with 5+ years of experience.
• Proficiency in CI/CD and DevSecOps for AI/ML systems.
• Experience with scalable deployment architectures for AI/ML and LLM workloads.
• Ability to define and track AI Ops KPIs including performance, reliability, and automation efficiency.
• Strong background in data pipeline integration and ML infrastructure management.
• Knowledge of AI governance, risk, security, and compliance frameworks.
• Experience in performance optimization for AI workloads (latency, cost, scalability).
• Ability to automate AI operations workflows and collaborate with cross-functional engineering teams.

Key Skills

Education

Any Gradute