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Strong employer brand, popular support/devops role, and Pune metro increase candidate density.
Core cloud and observability skills transfer across industries, but LLM-specific troubleshooting increases domain specificity.
Multiple explicit mandatory technical skills and experience requirements including cloud, observability, SQL, and LLM exposure.
Drive incident resolution, root-cause analysis, and performance optimization for Workday’s AI/ML platform and enterprise SaaS workflows.
Analyze system metrics, debug cloud-hosted ML service pipelines, inspect LLM orchestration layers, and manage critical customer escalations within SLAs.
Collaborate with engineering and data science teams on feature iteration, perform hands-on AI evaluation including reviewing LLM outputs, conversation logs, and system traces to identify failure modes and recommend improvements.
Minimum 1 year experience in technical support, platform operations, or application support for enterprise SaaS environments.
Minimum 1 year experience with SQL queries, API payload inspection (JSON or XML), basic Linux or Windows CLI tools, public cloud platforms (AWS, GCP, or Azure), and observability tools like Grafana or Kibana.
Minimum 1 year experience reviewing AI/LLM conversation logs, traces, or prompt outputs.
Willingness to work scheduled weekend and holiday rotations.
Experienced in diagnosing complex enterprise AI/ML workflows in cloud environments and performing incident management under strict SLAs.
Comfortable with hands-on analysis of AI model outputs and pipeline traces to improve system reliability and customer experience.
Able to communicate technical issues and resolutions effectively to customers and internal teams, and maintain detailed investigation documentation.