Product Support Engineer (SRE, QA)

• Own client-reported issues end to end: triage, troubleshoot, resolve, and close the loop
• Serve as a trusted technical point of contact for clients, translating complex problems into clear answers
• Dig into logs, metrics, APIs, and data to find root cause, not just the workaround
• Escalate and partner with engineering on product defects, with clean repro steps and context
• Build and maintain runbooks, knowledge base articles, and support documentation

• Monitor production health and respond to incidents across cloud environments (AWS/Azure)
• Implement proactive monitoring and alerting that catches issues before clients do
• Lead and contribute to blameless postmortems, and drive fixes to completion
• Automate repetitive support and operational tasks — if you've done it twice, script it
• Support secure, compliant, and resilient operations for clients in highly regulated industries

• Partner with product and engineering to test new features and releases before they ship
• Write and execute test plans, test cases, and regression suites
• Build and maintain automated tests and integrate them into CI/CD pipelines
• Turn real client issues into test coverage so the same bug never ships twice

• Use AI tools to speed up triage, troubleshooting, test generation, and documentation
• Help test and validate AI-powered product features, including output quality and edge cases
• Bring ideas for where AI can make our support and QA processes smarter

• 4+ years in technical product support, support engineering, or SRE roles
• 2+ years of hands-on QA experience, including manual and automated testing
• Hands-on experience with AWS and/or Azure
• Strong troubleshooting skills across logs, APIs, databases, and distributed systems
• Working knowledge of SQL and at least one scripting language – Python, Bash, or PowerShell experience preferred
• Experience with monitoring and observability tools – CloudWatch and Azure Monitor preferred
• Experience with test automation frameworks – Playwright experience preferred
• Familiarity with CI/CD pipelines and incident management practices
• Excellent communication skills, with the ability to explain technical issues to non-technical clients
• Strong multi-tasker, self-starter, and proactive team player

• Experience using or supporting AI/LLM-powered products, including testing AI outputs
• Highly regulated industry experience (e.g. finance, healthcare)
• Experience in consulting or client-facing delivery roles
• Kubernetes and Terraform experience
• Cloud certifications (AWS, Azure)
• Agile experience

Originally posted on Himalayas