Senior QA Search Engineer

Photon; Bengaluru; On-site; INR 2,600,000 - 4,200,000; Full time

Job summary

Photon is seeking a Senior Search QA Engineer to design, champion, and execute quality assurance for our enterprise search platform. You will validate index integrity, evaluate relevance algorithms, and ensure search clusters remain highly performant.

You will establish testing frameworks, leverage cloud infrastructure on GCP, and own end-to-end quality metrics while collaborating with engineers, product managers, and business stakeholders in an agile environment.

Qualifications

• 5+ years of software QA experience, with 2–3 years focused on specialized search platforms.
• Deep Apache Solr/Elasticsearch/Lucene expertise and debugging search queries.
• Hands-on testing in GCP or cloud platforms with relevant services.
• Proficient with Jira, Confluence, and agile metrics.
• Automation and scripting using Python, Java, or Bash.
• Experience with REST API testing and data validation using SQL.

Responsibilities

• Design, implement, and maintain QA strategy and automation for microservices and search architectures.
• Validate Solr configurations, schema updates, tokenizers, synonyms, boosting, and faceting.
• Monitor and analyze GCP performance and log data; ensure scale and failover.
• Architect Jira bug-tracking workflow with rich technical context.
• Create master test plans and QA runbooks in Confluence.
• Plan and execute load and performance testing on search APIs for sub-second latency.
• Mentor junior QA engineers and analysts.

Skills

QA Experience

Search platforms

Automation & scripting

API testing

SQL

Tools

Solr

Elasticsearch

GCP

Jira

Confluence

Postman/Newman

Job description

JobTitle: Senior Search QA Engineer

Role Overview

We are seeking an experiencedSenior Search QA Engineerto design, champion, and execute the quality assurance strategy for our enterprise search platform. Search at our scale is a complex ecosystem of data pipelines, distributed infrastructure, and real-time relevance tuning. In this role, you won't just look for broken buttons—you will validate index integrity, evaluate complex relevance algorithms, and ensure our search clusters remain highly performant.

As a senior member of the team, you will establish testing frameworks, leverage cloud infrastructure, and own the end-to-end quality metrics. You will be a vital bridge between search engineers, product managers, and business stakeholders, ensuring our agile delivery is both fast and flawless.

Key Responsibilities

• QA Strategy & Architecture:Design, implement, and maintain comprehensive test strategies and automation frameworksspecifically optimized for microservices and search architectures.

• SolrValidation & Relevance Testing:Validate complex ApacheSolrconfigurations, including schema updates, custom tokenizers, synonyms, boosting rules, and faceting behaviors. Ensure data consistency between source databases andSolrindexes.

• GCP Infrastructure & Log Analysis:Monitor and analyze system performance and error rates acrossGoogle Cloud Platform (GCP)using tools like Cloud Logging, Cloud Monitoring, andBigQuery. Validate that search clusters scale and failover smoothly.

• Agile Leadership & Jira Governance:Architect the bug-tracking workflow withinJira, ensuring defects are prioritized, tracked, and thoroughly documented with rich technical context (e.g., query explain plans, raw JSON payloads, and log traces).

• Knowledge Management:Author master test plans, automated QA runbooks, and search-relevance matrices inConfluenceto establish a single source of truth for platform quality.

• Performance & Load Testing:Plan and execute load, stress, and regression testing on search APIs to ensure sub-second latency under peak traffic conditions.

• Mentorship:Provide technical guidance, code reviews, and mentorship to junior QA engineers and analysts.

Required Skills & Qualifications

• Experience:5+ years of software quality assurance experience, with at least 2–3 years focused onspecialized search platforms, data pipelines,or large-scale distributed systems.

• AdvancedSolrExpertise:Deep understandingof ApacheSolr(or Elasticsearch/Lucene internals).Proven ability to debug complex search queries, analyze score explanations (debugQuery=true), and validate index schemas.

• GCP Proficiency:Hands-on experience testing applications deployed in Google Cloud Platform (or AWS/Azure equivalent), including working with GKE (Google Kubernetes Engine), Pub/Sub, and cloud-native logging/monitoring tools.

• Atlassian Suite Mastery:Advanced proficiency withJira(including custom filters, dashboards, and agile metrics) andConfluencefor maintaining engineering documentation.

• Automation & Scripting:Strong scripting/programming skills (Python, Java, or Bash)to build automated test scripts, parse heavy log files, and validate API endpoints.

• API & Data Testing:Expert-level familiarity with REST API testing tools(Postman, Newman)and strong SQL skills to verify data ingestion pipelines.

Nice-to-Have Attributes

• Experience implementing automated search relevance testing (e.g., using frameworks or scripts to measure NDCG, Precision, or Recall).

• Familiarity with CI/CD tools (GitHub Actions, GitLab CI, or Jenkins) to embed automated search tests into deployment pipelines.

• Understanding of e-commerce behavioral data, clickstream analysis, or basic machine learning concepts related to search (e.g., Learning to Rank).