Quality Assurance Engineer

QA Engineer AI/ML & Manual Testing

Location : Remote / Onsite - Panchkula

Experience :03 years

Department : Engineering

Remuneration : 4.26LPA (based on skills, experience, and interview performance)

About the Role

Were looking for a QA Engineer who blends manual testing expertise with AI/ML quality validation. Youll ensure our web applications, APIs, and AI/ML features are accurate, reliable, and safe to ship by validating requirements, data flows, automation logic, and user experiences.

Youll work closely with Product Owners, Developers, and Technical leads to align on quality goals, defi ne testable acceptance criteria, and drive defect resolution.

What Youll Do

Requirements & Task Analysis:

Collaborate with Product Managers and Engineers to validate requirements and edge cases before development (shift-left mindset).

Translate user stories and feature specs into clear, testable acceptance criteria.

Data Quality & Conflict Handling:

Evaluate data accuracy, consistency, and conflict handling across sources (e.g., inputs, outputs, model predictions).

Flag data quality issues and suggest improvements for robustness.

AI/ML Quality Validation:

Test AI/ML features for accuracy, bias, stability, and edge-case behaviour.

Evaluate automation accuracy and reliability of model outputs.

Defect Reporting & Quality Status:

Report defects with clear impact, risk, and reproducible steps.

Track and communicate QA metrics, known risks, and quality status to stakeholders.

Collaboration & Communication:

Work closely with Developers, Engineers, and Product Managers to align on quality goals and SLAs.

Facilitate clear, constructive communication on defects, risks, and quality improvements.

Must-Have Skills

12 years of experience in software QA with strong manual testing of web applications and APIs.

Solid understanding of QA fundamentals: test design, test planning, regression strategy, defect life cycle.

Exposure to AI/ML products as a tester or power user.

Ability to reason about expected model behavior and validate automation accuracy.

Strong attention to detail, curiosity, and willingness to challenge ambiguous behavior.

Clear written and verbal communication; able to write crisp bug reports and discuss issues with cross-functional teams.

Good-to-Have

Basic scripting (Python/JavaScript) for data manipulation and repeatable checks.

Experience with AI testing or monitoring tools.

Familiarity with CI/CD and integrating tests into pipelines.

What Success Looks Like

Requirements are validated early, reducing rework and ensuring clear acceptance criteria.

Data quality issues are identified and resolved proactively.

AI/ML features are validated for accuracy, reliability, and edge-case robustness.

Defects are reported with clear impact, risk, and reproducible steps.

Collaboration with Product, Development, and Tech teams ensures quality goals and SLAs are met.

About Us

We are an AI startup and realize that Natural Language isnt being understood by computers as sci-fi promised us. Started in 2014, Smarter. Codes earned clientele and appreciation from prestigious enterprises like Target Inc, Ford Motors, Tech Mahindra, Bank of Montreal, Delivery.com, TheMindGym, and likes. Bootstrapped during the fi rst 3 years of its inception, and angel funded in 2017. Smarter.Codes is navigated by 2 serial entrepreneur brothers and distinguished advisors across the globe - including mentors from the camps of 500 Startups, Alchemist Accelerator.

If you enjoy breaking complex systems, are curious about how AI/ML behaves in the real world, and love clear, impactful communication, this role is for you.