Job Overview
- Job Title: QA Engineer
- Function: Engineering – AI & Data
- Business Unit: REIL (Reliance Enterprise Intelligence Ltd)
- Location: Mumbai, India
- Experience: 4–6 Years
- Employment Type: Full-Time
- How to Apply: Send your resume directly to [email protected]
About REIL
Reliance Enterprise Intelligence Ltd (REIL) is a strategic joint venture between Reliance Industries and Meta. We combine Reliance’s unparalleled market scale and deep enterprise domain knowledge with Meta’s world-class AI and technology capabilities.
About the Programme
REIL is developing a cutting-edge enterprise AI platform focused on financial compliance and intelligence.
Role Overview
We are looking for a QA Engineer to own end-to-end testing across our entire platform. In a compliance-driven context, a software defect isn't just a technical glitch—it carries real financial and regulatory consequences.
You will be involved from the earliest stages of development, defining acceptance criteria, building automated test frameworks, and ensuring every component meets the stringent accuracy and reliability standards required before entering production compliance workflows.
Key Responsibilities1. Test Strategy & Planning
- Develop and own the overall test strategy for the platform, spanning data pipelines, ML models, APIs, application services, and frontend interfaces.
- Collaborate with Product Managers to define explicit acceptance criteria for user stories prior to development.
- Define precise accuracy and reliability thresholds required for ML models to be deemed production-ready.
- Maintain a living test plan that dynamically evolves alongside new product features and use cases.
2. Functional & Business Logic Testing
- Translate complex compliance rules and complex business logic into structured, executable test cases.
- Partner with domain subject matter experts (SMEs) to identify critical edge cases and exception scenarios.
- Validate AI-driven outputs (e.g., channel routing, classification recommendations, generated responses) against established compliance ground truths.
- Audit end-to-end workflows from initial data ingestion to user-facing outputs to ensure data integrity.
3. ML & AI System Testing
- Build robust regression test suites to ensure model retraining does not break existing correct behaviors.
- Evaluate model outputs for consistency, groundedness, and accuracy using a hybrid of automated evaluation and structured manual reviews.
- Validate fallback mechanisms to ensure graceful system degradation when model confidence is low or upstream services fail.
- Verify feedback loop integrity, ensuring validator decisions are accurately captured and routed back to retraining pipelines.
4. API & Integration Testing
- Construct and maintain comprehensive API test suites covering correctness, error handling, and extreme edge cases.
- Conduct load and performance testing on real-time inference endpoints to validate system behavior under production volumes.
- Test third-party and government portal integrations against documented API contracts, simulating failure and retry scenarios.
5. User Acceptance & Production Readiness
- Coordinate and facilitate User Acceptance Testing (UAT) with RIL compliance and assurance teams.
- Produce formal production readiness assessments prior to deployments, documenting test logs, pass rates, and residual risks.
- Monitor production defects and proactively manage the defect lifecycle through to resolution.
Qualifications & SkillsEducation
- B.E. / B.Tech / M.Tech in Computer Science, Information Technology, or a related technical field.
Required Experience
- 4+ years of QA engineering experience, including at least 2 years testing AI, ML, or data-heavy production systems.
- Proven track record of writing, deploying, and maintaining automated test frameworks (not just manual testing).
- Demonstrated ability to translate intricate business rules into clear, structured test cases.
Technical Skill Set
- Test Automation: Pytest, Selenium, Playwright, or equivalent for backend/frontend automation.
- API Testing: Postman, REST-assured, or equivalent; strong experience with contract testing.
- Performance Testing: Locust, JMeter, or equivalent for load and stress testing.
- Languages: High proficiency in Python for test scripting and automation.
- ML & Data Testing: Experience validating ML model outputs, building evaluation datasets, executing schema checks, and ensuring data pipeline completeness.
- CI/CD Integration: Hands-on experience integrating test suites into CI/CD pipelines for automated execution.
Preferred Qualifications
- Prior experience testing compliance, fintech, or legal technology systems where business logic accuracy is legally critical.
- Familiarity with modern LLM evaluation frameworks (e.g., RAGAS, TruLens).
- Experience with exploratory testing techniques specifically tailored for probabilistic AI system outputs.
- Prior exposure to highly regulated environments requiring formal sign-offs and meticulous test documentation.
Core Competencies
- Technical: Test Strategy & Planning | ML & AI System Testing | API & Integration Testing | Business Logic Validation | Test Automation
- Behavioral: Attention to Detail | Proactive Risk Identification | Cross-Functional Collaboration | Ownership & Accountability | Structured Problem Solving
To Apply
Interested candidates who meet the above criteria are invited to submit their updated resume to [email protected] with the subject line "Application for QA Engineer - REIL".
Pay: ₹310,933.20 - ₹1,800,000.00 per year
Benefits:
- Health insurance
- Paid sick time
- Provident Fund
Work Location: In person
