• Plan, test, and execute rolling upgrades of LLM runtimes, agent-orchestration frameworks, and supporting services

• Enforce IAM, secrets-rotation, data-classification, and Responsible-AI guardrails;

• Track license usage and optimise spend.

• Instrument Service Level Indicators (SLIs) (auth latency, inference success-rate) and uphold Service Level Objectives (SLOs);

• Analyze GPU/CPU utilisation, prompt accuracy, evaluation frameworks, vector-search query latency, and agent throughput;

• Implement auto-scaling policies, caching, and cost-control dashboards.

• Develop concise how-to guides and live workshops that upskill product squads on safe prompt engineering, RAG patterns, and platform APIs.

• Minimum requirement of 4 years of relevant work experience. Typically reflects 5 years or more of relevant experience.

• Typical requirements of 6 years in management and administration of Enterprise AI SaaS applications.

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