Karthik Raja V

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Professional Summary

Manager, Systems Automation with 10+ years in healthcare and MedTech quality engineering. At Johnson & Johnson, transformed Digital Surgery Platform testing from zero reliability to single-click execution across six teams (30+ engineers) on Azure cloud. Designed five platform-wide systems: unified Robot/pytest framework with CI, E2E performance testing scaling from 30 to 75,000+ concurrent devices, data platform test framework, automated daily reporting, and an AI Bug Analyser with CI + Jira integration. Drove shift-left testing, quality gates in CI pipelines, and test strategy ownership. Test coverage: 40% to 85%+. Cycle time: reduced 40%. Experienced in leading teams of SDETs for automated system-level Design Verification of FDA/ISO/IEC regulated medical devices.

Technical Skills

Test Frameworks: Robot Framework, Pytest, Pytest-BDD, Selenium, BDD/Gherkin, Cucumber, REST Assured, Postman

Programming: Python, Groovy, Bash, Shell Scripting, SQL

CI/CD & DevOps: Jenkins, Jenkins Pipeline-as-Code, Azure DevOps, Docker, Kubernetes, GitHub Actions, SonarQube

Cloud & Data: Azure Cloud, MySQL, Cosmos DB, Databricks, GraphQL, JFrog Artifactory

Testing Types: Systems Automation, Design Verification, Verification & Validation (V&V), Performance Testing, API Testing, Integration Testing, Regression Testing, Embedded Systems/Firmware Testing, Security Testing

Tools & Platforms: Jira, XRAY, Confluence, Git, Bitbucket, Allure Reports, CMake, Makefile

Methodologies: Agile (Scrum), SAFe, Shift-Left Testing, Continuous Testing, Risk-Based Testing, TDD, BDD

Domain & Compliance: ISO 13485, IEC 62304, FDA 21 CFR Part 11, FDA SOP Compliance, Healthcare/MedTech, IoMT, Medical Device Software (Class II/III)

Work Experience

• Lead a team of SDETs responsible for building automated verification frameworks for medical device system-level Design Verification, ensuring safety and effectiveness of products.
• Develop, validate, and release automated test frameworks for formal verification leveraging existing frameworks and industry best practices across FDA/ISO/IEC regulated products.
• Plan, prepare, and execute automated system-level tests for assigned projects during development and formal System Design Verification.
• Drive continuous optimization of automated test processes using risk-based analysis and statistical methods to maximize test efficacy while minimizing testing time.
• Oversee CI/CD integration for verification pipelines across multiple concurrent product initiatives, balancing competing needs for completion on time and budget.
• Lead hiring, staffing, and team development decisions; conduct periodic evaluations, mentor new staff, and improve team effectiveness.

• Restructured the complete test framework architecture across all DSP teams — transformed Robot Framework and pytest setups from zero reliability to single-click execution with full Jenkins CI integration, enabling unified test runs and reporting platform-wide.
• Created and owned the E2E performance testing framework for the DSP file pipeline — built realistic workload simulation with SQLite-based test files matching production device schema, high-scale parallel concurrency with adaptive worker controls, and DB-primary polling with API fallback. Scaled from 30 to 75,000+ concurrent devices. Reduced API calls by 95% (14,100 to 900 per 1,000-device test) and DB connections by 95% (1,000 to 50).
• Built comprehensive performance observability: per-stage/per-device latency distributions (p65/p95/p99/max/stdev), throughput metrics, error rates, Databricks Jobs API integration for task-level inspection, and automated HTML/Excel/JSON reporting with stage breakdowns and percentile views.
• Developed pipeline qualification script for Jenkins CI — automated pass/fail validation with entry/exit criteria enforcement, covering UI and API test execution per release. Enabled Test Quality (TQ) teams to rely on pipeline pass/fail reports with full traceability for every release cycle.
• Redesigned the Data Platform test framework using pytest, adopted across all teams as the standard for data pipeline validation and quality gates.
• Built automated daily report generation and distribution system with auto-trigger scheduling, delivering test execution reports to stakeholders at defined intervals.
• Architected the AI Bug Analyser system — integrated with CI pipelines and Jira, designed as a hooks-based architecture stashed within each team's repo, executing with minimal per-team changes (reference-only setup).
• Increased test coverage from ~40% to 85%+ through negative testing, risk-based strategies, and 150+ automated regression scenarios. Managed six testing teams (30+ engineers) across all releases.
• Modernized CI/CD pipelines for IoMT Embedded Device Agent SDK (C SDK): designed marker-based smart test execution across 224 BDD feature files and 64 test suites. Reduced pipeline configuration by 87% (4,704 lines to 631 lines). Created unified Jenkins prestage script serving all execution modes.
• Implemented dynamic Artifactory SDK overlay for on-demand released version testing and dynamic package versioning with Git commit SHA traceability.
• Drove shift-left testing and quality gate enforcement in CI pipelines; authored test strategy documents for every major release, presented to VP/Senior Director stakeholders.
• Mentored 30+ engineers on automation best practices, framework adoption, and AI tools; established onboarding standards for new QE team members across DSP.
• Led DB migration testing (Cosmos DB to MySQL), contributing to ~$500K in annual cost savings.

• Delivered E2E testing for Baxter Peritoneal Dialysis devices and New Product Development device under GDP guidelines.
• Designed 500+ test cases (BVA, equivalence partitioning, decision tables) and built Python + Selenium + BDD automation for 80+ critical scenarios.
• Authored ISO 13485-aligned verification artifacts and led ARB quality reviews; accelerated root cause analysis by 40% using Fishbone methods.

• Executed system integration and regression testing for hemodialysis software (Class II medical device, IEC 62304).
• Developed 200+ test cases for patient monitoring systems; automated workflows using Python, saving 15+ hours/sprint.
• Validated firmware updates on target hardware with zero field-reported critical defects.

• Managed calibration and preventive maintenance of 50+ biomedical devices (ventilators, monitors, infusion pumps). Implemented equipment tracking that reduced downtime by 20%.
• Supported critical-care equipment commissioning and contributed to NABH accreditation quality audits.

Key Achievements

• 5 platform-wide systems designed and delivered at J&J: test framework, performance framework, data platform framework, daily reporting, AI Bug Analyser.
• Test Coverage: 40% to 85%+ | Cycle time: 5 days to 1.5 days | Defect leakage: reduced 35%.
• Performance scale: 30 to 75,000+ concurrent devices (250x) | API pressure reduced 95% | DB connections reduced 95%.
• CI/CD modernization: 87% pipeline config reduction (4,704 to 631 lines) across IoMT SDK projects.
• Cost impact: ~$500K saved via Cosmos DB to MySQL migration.
• Strong/Strong rating in both 2024 and 2025 year-end evaluations at Johnson & Johnson.

Education

Languages

English | Tamil | Hindi | Malayalam