QA Manager – Hbox Platform and Applications
Company overview
HBox is a US Based Venture backed Digital Health Company. We enable Health Care Providers (HCP) to capture true Virtual Care Opportunities beyond Telehealth. We enable HCP to provide Proactive and Continuous Care and add new Recurring monthly revenue streams without any upfront cost. With our unique distribution and business model, we are seeing fast acceptance and great adaptation with our target customers.
We have built unique and Industry’s first Integrated Hardware, Cloud & AI Technologies based Virtual care Platforms for HCP Market. We are a US-focused Post revenue company with customers in 9 US States and growing fast. We provide an excellent opportunity to Innovate and work on cutting-edge product technologies in a very fast-moving dynamic and empowered environment.
Role Overview
We are seeking a seasoned QA Manager to lead quality engineering across our enterprise-grade, distributed application suite. You will own the end-to-end quality strategy for a complex, multi-tier ecosystem that spans relational databases, REST APIs, web portals, mobile applications, cloud-based services and AI agents — ensuring every release meets the highest standards of correctness, performance, security, and reliability. This is a player-coach role: you will lead and mentor a team of QA engineers while remaining hands-on with test strategy, tooling decisions, and GenAI-powered quality initiatives. Key Responsibilities
· Testing Strategy & Governance
ü Define and own the QA strategy across the full software delivery lifecycle for all application modules.
ü Establish testing standards, processes, and best practices across functional, non-functional, regression, sanity, smoke, integration, and end-to-end testing.
ü Maintain and continuously improve a living test plan aligned to product roadmap milestones.
ü Champion shift-left testing by embedding quality practices early in design and development.
· Functional & Non-Functional Testing
ü Functional Testing: Drive requirements-based test coverage across all business workflows spanning web portals, mobile apps, RESTful APIs, and AI agent interactions.
ü Non-Functional Testing: Plan and execute performance, load, stress, scalability, and security testing for distributed microservice architectures.
ü Regression & Sanity Testing: Maintain prioritised regression suites; enforce sanity gates at every CI/CD pipeline stage.
ü Integration Testing: Validate end-to-end data flows and contract compliance across relational databases, APIs, and third-party integrations.
· Test Automation
ü Architect and govern the enterprise automation framework across multiple technology layers:
· UI automation — web portals and mobile applications (Selenium, Playwright, Appium, Cypress, or equivalent).
· API automation — REST API contract and functional testing (Postman/Newman, RestAssured, Karate, or equivalent).
· Database validation — SQL-based data integrity checks and ETL pipeline verification.
· AI agent evaluation — automated correctness, safety, and regression harnesses for GenAI-powered features.
ü Define automation ROI metrics; continuously expand automation coverage and reduce manual regression effort.
ü Integrate test suites into CI/CD pipelines (Jenkins, GitHub Actions, GitLab CI, or equivalent).
· GenAI-Powered Quality Engineering
ü Leverage Generative AI tools (e.g., GitHub Copilot, Cursor, Claude, ChatGPT, or specialised QA AI tools) to accelerate test case generation, script authoring, and defect analysis.
ü Design evaluation frameworks for AI/ML feature quality: prompt regression testing, output correctness scoring, bias and hallucination detection.
ü Identify and adopt emerging GenAI-based QA tooling to improve team velocity and coverage.
ü Define guardrails for responsible AI use in the QA process.
· Team Leadership & Cross-Functional Collaboration
ü Hire, mentor, and manage a team of SDET and QA engineers; provide clear career development paths.
ü Partner with Engineering, Product, and DevOps to embed quality at every stage of the SDLC.
ü Drive defect triage, root-cause analysis, and quality retrospectives.
ü Report quality KPIs (defect escape rate, automation coverage %, cycle time, mean-time-to-detect) to senior leadership.
· Technical Expertise Required
Category
Scope/ Examples
Application Components
Relational databases (PostgreSQL, MySQL, Oracle), REST APIs, web portals (React/Angular), iOS & Android mobile apps, AI/LLM agents
Test Types
Functional, regression, sanity/smoke, integration, E2E, performance/load, security, API contract, database, AI agent evaluation
Automation Frameworks
Selenium, Playwright, Cypress, Appium, RestAssured, Postman/Newman, Karate, JMeter, Gatling, or comparable enterprise-grade tools
CI/CD & DevOps
Jenkins, GitHub Actions, GitLab CI, Docker, Kubernetes; experience with blue/green and canary deployments
GenAI Tools
AI code assistants (Copilot, Cursor), LLM-based test generation, AI defect triage tools; ability to build prompt evaluation harnesses
Languages & Scripting
Proficiency in Java, Python, JavaScript/TypeScript, or comparable; SQL for database validation
Test Management
Jira/Xray, TestRail, Zephyr, or equivalent; strong defect lifecycle management
Required Qualifications
· 8+ years in software quality assurance, with 3+ years in a QA lead or management role.
· Demonstrated experience testing distributed, multi-module enterprise applications.
· Hands-on background in building and scaling test automation frameworks (UI, API, and/or database).
· Strong understanding of modern CI/CD practices and DevOps toolchains.
· Proven track record owning QA for RESTful microservices and relational database systems.
· Experience with performance/non-functional testing tools and methodology.
· Excellent communication skills; ability to present quality metrics to technical and non-technical stakeholders.
Preferred Qualifications
· Experience testing mobile applications (native iOS/Android, Flutter) and responsive web applications.
· Hands-on use of Generative AI tools for QA tasks (test generation, script authoring, root-cause analysis).
· Exposure to evaluating or testing AI/ML models, agents, or LLM-powered features.
· ISTQB Advanced Level or equivalent certification.
· Experience with security testing concepts (OWASP, SAST/DAST) and accessibility testing (WCAG).
Background in Agile/SAFe delivery at scale.
Pay: ₹476,008.09 - ₹2,500,000.00 per year
Benefits:
- Paid sick time
- Paid time off
- Provident Fund
Work Location: In person
