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Staff QA Automation Engineer
Posted by Meeru AI on 9 October 2026. Still on their Workable board when we checked 1 h ago.
Read out of the posting
LevelNot stated
Experience askedNot stated
EmploymentNot stated
LocationHyderabad, Sindh, Pakistan
RemoteNot stated
Visa sponsorshipNot stated
SalaryNot published, and most postings do not
Posted2026-10-09
Found viaworkable, direct from their system
We saw it 1 day after it went up.
The posting, as the company wrote it
Employment: Other
Experience: Mid-Senior level
Meeru AI is building an AI-native platform that transforms how finance and accounting teams operate. We connect to enterprise financial systems — ERPs, CRMs, billing platforms, HRIS — and apply machine learning to turn fragmented operational data into grounded, auditable intelligence for CFOs, controllers, and FP&A leaders.
We deploy on customer terms — SaaS multi-tenant, SaaS single-tenant, and on-premises — across AWS, Azure, and GCP . Our customers are Fortune 500 finance teams who require data isolation, auditability, and compliance.
Requirements
8+ years in QA and test automation, including 3+ years leading people. You've hired, run 1:1s and performance reviews, and mentored QA engineers, not just led a project.
You've built automation frameworks from scratch. You've taken a product from little or no automation to a working framework across API, UI and backend tests, and you can explain the design choices.
Strong coding in Python and JavaScript/TypeScript. You write maintainable test code daily in both: PyTest for the backend, TypeScript for the frontend.
Deep API testing experience. REST, GraphQL and WebSockets, using tools like PyTest, Postman or REST Assured, including contract, negative and auth testing.
Modern end-to-end UI testing. Playwright or Cypress against React/Next.js apps, with reliable, low-flake suites covering critical user journeys.
Backend and database testing. Testing Python/FastAPI services and PostgreSQL (SQLAlchemy), with SQL-based data validation and attention to database performance.
CI/CD integration. You've wired tests into GitHub Actions, Jenkins or GitLab CI, set up deployment quality gates, and worked with Docker/Kubernetes environments.
Performance and load testing. You've designed load, stress and scalability tests with tools like k6, Locust or JMeter, plus front-end checks like Lighthouse.
Security testing. SAST/DAST in the pipeline (e.g. SonarQube, Snyk, OWASP ZAP, Burp Suite), and testing authentication, role-based access and data encryption.
Multi-tenant SaaS experience. You've tested platforms where many customers share infrastructure and know how to prove one tenant can't see another's data.
Compliance-driven testing. You've supported SOC 2, GDPR or HIPAA requirements with test processes and evidence.
Cloud experience. AWS preferred (EC2, ECS, EKS, Lambda); GCP or Azure also welcome.
Quality leadership and process. You've defined QA standards, metrics and KPIs, release and regression procedures, and runbooks, and you report quality clearly to leadership.
Clear communication and collaboration. You work closely with Product on acceptance criteria, Engineering on testability and DevOps on releases, explaining risk to technical and non-technical people alike, in an Agile/Scrum setup.
Nice-to-haves
Testing AI/LLM applications. You've tested LLM features or agentic workflows, can handle non-deterministic output, validate prompts and model outputs, and check for bias and fairness. LangChain/LangGraph familiarity is a plus.
FinTech or financial services background. Experience where accuracy, audit trails and reliability around money matter.
Startup experience. You're comfortable building from zero in a fast-moving, ambiguous environment.
Observability and production monitoring. Datadog, CloudWatch, Prometheus or New Relic, including monitoring AI behavior in production.
Chaos engineering and resilience testing.
Test management tools. TestRail, Zephyr or Jira-based test management.
Certifications. ISTQB Advanced (or similar), AWS Certified Developer or Solutions Architect.
Community involvement. Open-source contributions to testing frameworks, technical writing or conference talks.
Also open at Meeru AI
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