Support Engineer

We are seeking a customer-focused Support Engineer to drive incident resolution, root-cause analysis (RCA), and performance optimization across Workday’s enterprise platform and autonomous AI agent workflows.

In this high-visibility role, you will analyze system metrics, debug cloud-hosted ML service pipelines, inspect LLM orchestration layers, and manage critical customer escalations within strict SLAs.

You will also partner directly with engineering and data science teams through feature iteration and optimization.

A key part of this role involves hands-on AI evaluation: analyzing LLM outputs, reviewing conversation logs, and digging into system traces to spot failure modes and translate those insights into prompt, data, and workflow improvements.

Key Responsibilities

• Enterprise SaaS & Functional Domain Expertise: Apply foundational knowledge of enterprise applications to validate AI responses and assist in troubleshooting functional processing errors.
• Hands-On AI Evaluation: Review LLM outputs, conversation logs, and execution traces to identify edge cases, hallucinations, and routine failure modes.
• Technical Troubleshooting & RCA: Assist in root-cause analysis for software defects and pipeline execution failures using monitoring tools like Kibana and Grafana.
• Cloud & LLM Diagnostics: Inspect enterprise AI workflows hosted in public cloud environments (AWS, GCP).
• Incident & Queue Management: Monitor and triage support queues, enforce SLAs, and process incoming tickets efficiently.
• Customer Communication: Communicate clear technical updates, standard workarounds, and resolution steps to customer IT teams.
• Database & Code Diagnostics: Write standard SQL queries to validate backend data integrity, inspect REST/SOAP API payloads (JSON/XML).
• Documentation & Team Collaboration: Maintain detailed investigation logs in Jira, ServiceNow, or Salesforce.

Basic Qualifications (Required)

• Work Experience: Minimum 1 year of experience in technical support, platform operations, or application support for enterprise SaaS environments.
• Technical & Diagnostic Skills: Minimum 1 year of experience writing and executing intermediate SQL queries and running diagnostic scripts.
• Cloud & Monitoring Systems: Minimum 1 year of hands-on experience navigating or monitoring services on public cloud platforms (AWS, GCP, or Azure).
• AI & LLM Exposure: Minimum 1 year of experience inspecting, reading, or evaluating AI/LLM conversation logs, traces, or prompt outputs.
• Triage & Operations: Minimum 1 year of experience performing initial queue triage and basic troubleshooting using ticketing workflows.

Preferred Qualifications

• Bachelor’s degree in Computer Science, Information Technology, Engineering, or a related technical field (or equivalent practical work experience).
• Experience following established runbooks to perform guided, autonomous technical troubleshooting.
• History of drafting clear written technical documentation, post-incident updates, or resolution notes for customer-facing teams.