Sr. QA Engineer(SDET-Java), GenAI/AI Platform

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This position is located in Pune. Youll be working in a major tech center of Pune, India. Across the globe, our Centers of Energy serve as hubs where we accelerate productivity and collaboration, inspire creativity, and cultivate a culture of connection and celebration. Our teams coordinate their time in Centers of Energy to reflect how they work best.
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What Youll Do:
LogicMonitorregistered is the AI-first hybrid observability platform powering the next generation of digital infrastructure. LogicMonitor delivers complete visibility and actionable intelligence across on-premises, cloud, and edge environments. By anticipating issues before they strike, optimizing resources in real time, and enabling faster, smarter decisions, LogicMonitor helps IT and business leaders protect margins, accelerate innovation, and deliver exceptional digital experiences without compromise.
Our customers love LogicMonitors ability to bring cloud and traditional IT together into one view, as seen in minimal churn rates, expansion business, and exciting new customer references. In fact, LogicMonitor has received the highest Net Promoter Score of any IT Infrastructure Management provider. LogicMonitor also boasts high employee satisfaction. We have been certified as a Great Place To Workregistered, and named one of BuiltIns Best Places to Work for the seventh year in a row!
LogicMonitor is looking for a highly skilled SeniorQA/SDET with 4 to 5 years of experience to build and scale automated test frameworks for Generative AI features across our observability platform. In this role, you will ensure the quality, reliability, safety, and performance of LLM-based workflows, including AI assistants, Retrieval-Augmented Generation (RAG) pipelines, AI-generated incident summaries, auto-remediation agents, tool calling, and AI-driven insights. You will work closely with engineering, product, and applied AI teams to validate AI experiences in production.
Heres a closer look at this key role:

• 1. Test Strategy for GenAI Features
• Define end-to-end test strategies for GenAI-driven product features, including:
• AI assistant chat flows (multi-turn conversations)
• AI-generated RCA summaries and incident timelines
• RAG-based responses using knowledge base, tickets, and observability signals
• Agent execution flows (tool calling, action orchestration)
• Establish quality standards for AI output across:
• Factuality, relevance, completeness, groundedness
• Hallucination risk mitigation
• User trust and explainability
• Automation Framework & End-to-End Testing
• Build scalable automation test frameworks for API and UI experiences.
• Automate validation of:
• AI endpoints (REST / GraphQL)
• Orchestration workflows
• Streaming behaviors
• Structured response schemas (JSON, Pydantic models, etc.)
• Develop regression test packs that run in CI/CD pipelines and validate:
• Deterministic system behavior around non-deterministic model outputs
• AI Evaluation (LLM Testing)
• Create and maintain LLM evaluation test suites, including:

• Golden datasets (prompt → expected response patterns)
• Rubric-based scoring (LLM judge + deterministic validation checks)
• Failure taxonomy (hallucinations, irrelevant retrieval, refusal bugs, etc.)
• Build automated pipelines for:
• Drift testing
• Prompt regression testing
• Retrieval quality regression testing
• Reliability, Performance & Scale Testing
• Design and implement performance and load tests for:
• High concurrency chat experiences
• Streaming response latency
• Tool execution latency
• RAG query throughput
• Ensure AI systems consistently meet SLOs and performance targets.
• Safety, Security & Compliance Testing
• Validate AI system robustness against:
• Prompt injection attacks
• System prompt leakage
• Cross-tenant data access risks
• Unsafe tool execution
• PII and sensitive data exposure
• Build guardrail validation tests for:
• Safe refusal behavior
• Policy compliance
• Approval flows for state-mutating agent actions
• Observability & Debuggability for AI Testing
• Collaborate with engineering teams to enhance AI observability:
• Tracing across agents and tool calls
• Prompt and tool execution logging
• Retrieval traceability logs
• Model output diffing
• Use monitoring and telemetry to detect regressions and report actionable issues.
  

What Youll Need:

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Get Hired

• 4 to 5 years of experience as an SDET / QA Automation Engineer
• Strong programming skills in Python or Java
• Strong hands-on automation experience with:
• API testing frameworks (PyTest, Requests, RestAssured, etc.)
• UI testing frameworks (Playwright / Cypress / Selenium)
• CI/CD automation (GitHub Actions / Jenkins)
• Strong understanding of:
• Microservices and distributed systems testing
• Asynchronous workflows and queues
• Cloud-native architecture and reliability testing
• Proven ability to build test strategies for:
• Functional, regression, integration, contract, and performance testing
• Experience testing LLM-based systems, such as:
• AI assistants (multi-turn chat)
• RAG pipelines
• Agentic workflows (tool calling, orchestration)
• Strong understanding of common GenAI failure patterns:
• Hallucinations
• Prompt injection
• Retrieval failures
• Toxicity and unsafe responses
• Ability to create evaluation datasets and rubrics for AI correctness
  

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LogicMonitor is an Equal Opportunity Employer
At LogicMonitor, we believe that innovation thrives when every voice is heard and each individual is empowered to bring their unique perspective. Were committed to creating a workplace where diversity is celebrated, and all employees feel inspired and supported to contribute their best.
For us, equal opportunity means fostering a truly inclusive culture where everyone has the chance to grow and succeed. We dont just open doors; we invite you to step through and be part of something bigger. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran.
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