Full-Time
Quality Assurance Automation Engineer
Posted on 8/22/2026
Phizenix
No salary listed
Hyderabad, Telangana, India
Hybrid
Category
 QA & Testing (1) |
|---|
Required Skills
LLM
Datadog
Kubernetes
Microsoft Azure
Agile
FastAPI
Python
JavaScript
React.js
GitHub Actions
Software Testing
Git
SonarQube
Jest
SQL
Postgres
GraphQL
Docker
Quality Assurance (QA)
TypeScript
SOC 2
AWS
JIRA
Mocha
Prometheus
New Relic
LangGraph
Jenkins
Next.js
Playwright
SCRUM
REST APIs
LangChain
Selenium
DevOps
HIPAA
Google Cloud Platform
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Requirements
- 10+ years of QA or test automation experience, including 3+ years in leadership.
- Expert-level test automation skills across API, UI, and backend testing.
- Strong programming skills in Python and JavaScript or TypeScript.
- Proven experience building test automation frameworks from scratch.
- Deep knowledge of functional, integration, end-to-end, and performance testing methodologies.
- Expertise integrating automated tests into continuous integration and continuous delivery pipelines.
- Expertise testing REST, GraphQL, and WebSockets APIs.
- Experience with Python, FastAPI, PostgreSQL, and SQLAlchemy for backend testing.
- Experience with React, TypeScript, Playwright, or Cypress for frontend testing.
- Experience with load testing, stress testing, and scalability validation.
- Experience with static application security testing, dynamic application security testing, and vulnerability scanning.
- Experience with SQL, data validation, and database performance testing.
- Experience with AWS, GCP, or Azure cloud platforms.
- A proven track record of building QA teams of at least three people.
- Experience establishing QA processes and standards from scratch.
- Experience with compliance testing for SOC 2, GDPR, or HIPAA.
- Experience with Agile or Scrum methodologies.
Responsibilities
- Design and implement a comprehensive test automation framework.
- Build API test automation for REST and GraphQL.
- Implement frontend end-to-end testing using Playwright and Cypress.
- Create backend and integration test suites.
- Establish continuous integration and continuous delivery integration for automated testing.
- Define the test data management strategy.
- Implement performance and load testing frameworks.
- Build and lead the QA team, initially comprising 2-5 engineers and scaling to 8-10.
- Define QA processes, standards, and best practices.
- Establish quality metrics and key performance indicators.
- Conduct one-on-one meetings and performance reviews.
- Mentor QA engineers on automation and testing practices.
- Drive quality culture across engineering.
- Develop testing strategies for large language model-powered features.
- Test agentic workflows and AI decision-making.
- Validate model outputs and prompt engineering.
- Test AI accuracy, consistency, and edge cases.
- Implement monitoring for AI behavior in production.
- Ensure responsible AI practices covering bias and fairness.
- Implement security testing, including static and dynamic application security testing.
- Test authentication, authorization, and role-based access control.
- Validate data encryption and privacy controls.
- Ensure SOC 2 and GDPR compliance requirements.
- Coordinate penetration testing.
- Test multi-tenant isolation and security.
- Define release testing procedures.
- Implement smoke and regression test suites.
- Validate staging and production deployments.
- Coordinate with DevOps on deployment gates.
- Perform post-deployment validation and monitoring.
- Partner with Product on acceptance criteria.
- Work with Engineering on testability.
- Report quality metrics to leadership.
- Identify and escalate critical issues.
- Document testing processes and runbooks.
- Assess the current testing landscape and create a comprehensive QA strategy.
- Implement an API test automation framework with at least 50 test cases.
- Set up an end-to-end testing framework with critical-path coverage.
- Integrate automated tests into the continuous integration and continuous delivery pipeline.
- Hire 1-2 QA engineers.
- Establish the test data management approach.
- Define quality metrics and key performance indicators.
- Achieve 70% or greater API test coverage.
- Achieve 60% or greater end-to-end test coverage for critical user flows.
- Build the QA team to 3-4 engineers.
- Implement a performance testing framework.
- Establish security testing practices using static and dynamic application security testing.
- Reduce production defects by 40%.
- Implement an AI/ML testing strategy for large language model features.
- Achieve less than 10-minute test execution time in continuous integration and continuous delivery.
- Scale the QA team to 5-8 engineers.
- Achieve 80% or greater overall test coverage.
- Reduce the production defect escape rate to less than 5%.
- Implement continuous testing with less than 15-minute feedback loops.
- Establish quality gates for all releases.
- Achieve a 99.5% or greater test pass rate.
- Build comprehensive test documentation and runbooks.
- Establish SOC 2-compliant testing processes.
Desired Qualifications
- Experience testing large language model applications or AI/ML systems.
- Knowledge of prompt engineering and model validation.
- Understanding of AI testing challenges, including non-determinism and bias.
- Familiarity with LangChain, LangGraph, or similar frameworks.
- Startup experience and ability to work in a fast-paced environment.
- FinTech or financial services domain knowledge.
- ISTQB Advanced or similar certification.
- AWS Certified Developer or Solutions Architect certification.
- Experience with chaos engineering and resilience testing.
- Knowledge of observability tools such as Datadog and New Relic.
- Open-source contributions to testing frameworks.
- Technical writing or conference speaking experience.