Test Engineer

Role Title: QA / Test Engineer Technical & Functional

Location: Jaipur

Platform: Databricks Lakehouse (Unity Catalog, Mosaic AI, Databricks Apps, Delta Live Tables, Jobs
& Pipelines)

Experience: 3–7 years in QA/Test Engineering, with hands-on data & AI/agent testing exposure

About the Role:

We are building multi-agent, AI-powered Frameworks on
Databricks. The framework is composed of specialised AI agents surfaced through
a React + FastAPI portal on Databricks Apps, with governed approvals and Entra
ID/RBAC security.

We're looking for a QA / Test Engineer who is equally
comfortable validating the technical correctness of data pipelines, agent logic
and APIs, and validating that the framework behaves correctly from an end-user
and business-rule perspective. This is a dual-mandate role: Technical
(Backend/Data/AI) Testing + Functional (Business Rule/UAT) Testing.

Required Skills & Experience

3–7 years of QA/Test Engineering experience, including at least 1–2 years testing
data platforms, data pipelines, or AI/ML-driven systems.

Strong SQL skills for data validation, reconciliation, and writing independent test
queries against Unity Catalog / Delta tables.

Working knowledge of Databricks (Notebooks, Jobs, Unity Catalog, Delta Lake/Delta Live
Tables) or a comparable Lakehouse/Spark platform.

API testing experience (Postman/REST-assured/pytest or similar) for validating
FastAPI/microservice endpoints.

Exposure to testing AI agent / LLM-based systems (prompt-response validation,
hallucination/guardrail checks, NL-to-SQL accuracy testing) is highly valued.

Experience with RBAC/identity testing (Entra ID, SSO, or equivalent) and
governance/approval workflow testing (ServiceNow ITSM or similar ITSM tools).

Familiarity with test management and defect tracking tools (Jira, Azure DevOps, TestRail,
or equivalent).

Basic scripting ability (Python or PySpark) to validate transformation logic and
build lightweight test automation.

Solid understanding of SDLC/Agile delivery, UAT coordination, and writing clear,
traceable test documentation.

Strong analytical mindset with the ability to read technical architecture and
translate it into concrete test scenarios spanning both back-end pipelines and
front-end/business behavior.

Good to Have

Prior experience testing multi-agent or orchestrated AI systems.

Exposure to ServiceNow, Oracle ERP, or SAP source data and their common data quality
issues.

Experience with performance/load testing tools (JMeter, Locust, or similar).

Familiarity with CI/CD pipelines (Azure DevOps, GitHub Actions) for automated regression
testing.

Databricks or cloud (Azure) certifications.

What Success Looks Like

Zero critical defects escaping production across both milestones.

100% traceability between acceptance criteria (AC-1–AC-10) and executed test cases.

A regression suite that reliably validates rule execution, diagnosis, RCA,
self-healing, and reporting after every change.

Clean, audit-ready sign-off documentation for governance and steward-facing
capabilities.

Why Join

You'll work at the intersection of data engineering
and applied AI testing a real multi-agent system that makes autonomous
diagnostic and remediation decisions, not just a conventional CRUD application.
You'll shape the quality bar for a framework that directly governs enterprise
data trust across ServiceNow, Oracle, and SAP data.