Sr Associate Support Engineer

About the Role

We are seeking a customer-focused Support Engineer who is excited about supporting AI/ML/SaaS functionality and platforms and passionate about helping customers solve complex problems. In this high-visibility, customer-facing role, you will manage a ticket queue of cases with varying complexity specifically for Adaptive Planning's Financial and Workforce Planning products. You will drive incident resolution, root-cause analysis (RCA), and performance optimization across both Workday Adaptive Planning's enterprise web applications and autonomous AI agent workflows. Partnering closely with product and support analyst teams, you will help customers find timely workarounds and solutions while managing critical escalations within strict SLAs. A key part of this role will also involve hands-on technical debugging and AI evaluation. You will analyze system metrics, debug cloud-hosted ML service pipelines, inspect LLM orchestration layers, review conversation logs, and dig into system traces to spot failure modes—translating those insights into prompt, data, and workflow improvements.

Location

• This position is based in the Workday Pune office. Candidates should be local to the Pune area or willing to relocate.
• Hybrid Work: Candidates will be expected to work from the office at least 50% of the time.
• Hours: Typical shift will be from 8:00 AM - 5:00 PM IST
• On-Call: Participation in an on-call rotation is required to provide after-hours support when needed.

Key Responsibilities

• Core Planning and Reporting Troubleshooting: Troubleshoot with customers on cases to resolve reported issues with their financial data, reporting, and/or financial integrations.
• 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. Perform structured data labeling and report findings to senior engineering staff.
• Technical Troubleshooting RCA: Assist in root-cause analysis for software defects and pipeline execution failures using monitoring tools like Kibana and Grafana, following established diagnostic runbooks.
• Cloud LLM Diagnostics: Inspect enterprise AI workflows hosted in public cloud environments (AWS, GCP), helping isolate breakdown points across model hosting services and API gateways.
• Incident Queue Management: Monitor and triage support queues, enforce SLAs, and process incoming tickets efficiently. Support high-severity incident responses and participate in weekend on-call rotations.
• Customer Communication: Communicate clear technical updates, standard workarounds, and resolution steps to customer IT teams, working with senior support for high-stakes escalations.
• Database Code Diagnostics: Write standard SQL queries to validate backend data integrity, inspect REST/SOAP API payloads (JSON/XML), and execute existing Python or Bash scripts to run routine diagnostics.
• Documentation Team Collaboration: Maintain detailed investigation logs in Jira, ServiceNow, or Salesforce, help maintain team runbooks, and flag recurring issue trends to senior engineers and product teams.

Requirements & Tech Stack

• 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.
• API Payload Inspection: Minimum 1 year of experience inspecting API payloads (JSON or XML data structures).
• Command-Line Tools: Minimum 1 year of experience utilizing basic Linux or Windows command-line tools.
• Cloud Monitoring Systems: Minimum 1 year of hands-on experience navigating or monitoring services on public cloud platforms (AWS, GCP, or Azure).
• Observability Tools: Minimum 1 year of experience utilizing observability tools (e.g., Grafana, Kibana, Datadog) to view logs or trace outputs.
• 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.
• Ability to manage multiple cases at once with some to no guidance around prioritization.
• Willingness and ability to work scheduled weekend and holiday coverage rotations.

Qualifications (Preferred)

• 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.
• Strong active problem-solving skills and an adaptability to learn complex, multi-tiered enterprise systems.
• Strong written and verbal communication skills, combined with the ability to communicate with users at all levels and varying technical ability.
• Experience collaborating with internal development and/or QA teams, acting as a customer advocate.
• Previous experience or knowledge of finance and/or financial planning software applications or integrations.
• ETL, tools (e.g., Pentaho) or Integration Implementation/Support
• Jenkins
• Git
• Kubernetes and Docker
• ELK or other log aggregation tool
• JavaScript