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QA Automation Engineer with 6+ years in scalable test automation frameworks & machine learning syste
Results-driven AI/ML QA Automation Engineer with 6+ years of experience designing and delivering scalable test automation frameworks for web, API, and machine learning systems. Proven expertise in end-to-end ML quality assurance – spanning model performance validation (accuracy, precision, recall, F1), data and concept drift detection, bias/fairness evaluation, adversarial robustness testing, and LLM prompt guardrail validation. Adept at building CI/CD-integrated quality gates that reduce regression cycle times, eliminate production defects, and accelerate release confidence. Recognised for achieving 90%+ automation coverage and driving measurable reliability improvements across Agile, product-led engineering teams. Passionate about embedding quality at every stage of the ML lifecycle – from data ingestion to model deployment and monitoring.
NMAMIT, Nitte (Nitte University)
Bachelor of Engineering (B.E.) · Information Science & Engineering
N/A – June 30, 2019
Conduent Business LLP
Quality Automation Engineer
September 1, 2022 – Present
Bengaluru, Karnataka, India
Micro Technoid Pvt. Ltd.
Test Engineer
October 1, 2019 – May 1, 2022
Bengaluru, Karnataka, India
CIGNA Healthcare - Data Quality & Compliance Automation
June 15, 2026 – Present
Automated patient data processing workflows using Python and Robot Framework with integrated data quality checks and PII validation logic; improved compliance test pass rates by 15% and enhanced data governance across regulated healthcare workflows.
Walmart - E-Commerce Platform
June 15, 2026 – Present
Engineered Robot Framework and PyTest automation suites with end-to-end API validation and performance baselines using JMeter; improved checkout flow stability, cut regression time by 40%, and proactively caught critical pricing and caching defects ahead of release.
Make One's Way Support Service - End-to-End Test Coverage
June 15, 2026 – Present
Executed manual, automated, API, and JMeter performance testing for a support services platform; centralised regression suites and data validation pipelines, significantly increasing test coverage and reducing defect escape to UAT.
Python and Playwright for Web & API Automation
Unknown
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's project diversity, spanning e-commerce, healthcare, and support services, indicates adaptability and a broad understanding of different business domains. Their experience in AI/ML QA, a rapidly evolving field, suggests a proactive and learning-oriented mindset. The emphasis on collaboration with developers and product owners in Agile settings further supports a strong cultural fit for dynamic engineering teams. The breadth of skills, from traditional test automation to advanced AI/ML quality assurance, shows a versatile and growth-oriented professional.
Soft Skills & Operational Fit
The candidate demonstrates strong operational fit through their experience in Agile environments, leading shift-left quality initiatives, and mentoring junior engineers. Their professional summary highlights a results-driven approach and a passion for embedding quality, indicating good alignment with collaborative and quality-focused teams. The detailed impact metrics provided in the resume suggest a focus on measurable outcomes and continuous improvement.