- Deploy and manage LLM-based applications across cloud and hybrid environments.
• Build and maintain production-grade inference pipelines for LLM workloads.
• Design and implement LLMOps pipelines for model, prompt, and configuration lifecycle management.
• Implement monitoring for latency, throughput, cost, errors, drift, and hallucinations.
• Build dashboards and alerts to ensure SLA and reliability targets.
• Optimize inference cost and performance using caching, batching, routing, and autoscaling strategies.
• Enforce security, access control, audit logging, and governance controls for LLM usage.
• Collaborate with Responsible AI teams to operationalize safety and compliance guardrails.
• Enable AI Engineers and Fullstack teams through reusable LLMOps frameworks and platforms.