Suresh Babu

Quality Engineering professional with 16+ years of experience across Asset Management, Maritime and Healthcare domains. Extensive expertise in Web (GUI), Mobile, API, Database, Integration, Performance and End-to-End Testing for enterprise applications. Experienced in all phases of the Software Development Life Cycle (SDLC), including requirements analysis, test strategy development, automation framework design, test execution, defect management and quality reporting.

Strong background in Agile and DevOps environments with hands-on experience in delivering scalable test automation solutions using Playwright, Selenium, Cypress, REST Assured, Python, TypeScript and Azure DevOps. Skilled in Quality Engineering best practices, test planning, risk-based testing, CI/CD integration, test data management and automation-first delivery approaches. Proven ability to lead testing efforts, improve release quality and collaborate effectively with cross-functional teams in fast-paced environments.

Hands-on exposure to Generative AI technologies, including Prompt Engineering, AI-Assisted Test Automation, LLM Evaluation. Possess strong domain expertise in Asset Management and trading platforms. Additionally, have extensive Healthcare domain experience with claims processing, member and provider systems, healthcare regulations, HIPAA compliance and interoperability standards.

Well-versed in enterprise-scale testing methodologies, system integrations and business-critical application validation.

Senior Automation Engineer (SDET) - ABS

(2023-08)

The American Bureau of Shipping (ABS) is an American maritime classification society established to promote the security of life, property and the natural environment, primarily through the development and verification of standards for the design, construction and operational maintenance of marine and offshore assets.

• Integrated the Playwright MCP Server into our AI development environment (VS Code). I configured a system prompt pinned with our team's exact TypeScript conventions, forcing the AI to format all generated assertions into our existing Page Object Model (POM) structure.
• Led a team of QE Automation Engineers in developing and implementing a test automation framework for a new maritime navigation system. The framework resulted in a 25% reduction in the time it took to execute regression tests.
• Designed and executed automated tests for a new maritime cargo booking system. The tests helped to identify and fix critical defects before the system was released to production.
• Leveraged Prompt-Driven Development techniques to accelerate Playwright automation script creation, API test generation and test data preparation.
• I automated the generation of boilerplate test scripts by integrating OpenAI's API into our local IDE environment via a custom script.
• Perform API testing using GraphQL (GQL) to validate data integrity and communication between various ABS systems and applications.
• Perform Load Testing using Azure Load Testing (ALT) to simulate heavy loads and stress on ABS applications, ensuring their performance and scalability meet industry standards.
• Integrated AI-assisted test generation techniques to create automated test scenarios from user stories and requirements.
• Performance testing using JMeter to identify bottlenecks, assess system performance and optimize critical maritime systems.
• Verified the integrity of Nautical data using Azure Cosmos DB, validating data storage and retrieval processes to different PODS within the project.
• Integrated automated tests into the CI/CD pipeline, ensuring that every code change is thoroughly tested before deployment.
• Developed and optimized structured prompts for AI-assisted test case generation, defect analysis and requirements validation.
• Designed reusable prompt templates to improve consistency and accuracy of test scenarios generated by Large Language Models (LLMs).
• Evaluated prompt effectiveness using response quality metrics, reducing manual test design effort by 40%.
• Validated Large Language Model (LLM) responses for accuracy, relevance, consistency and hallucination detection.

Senior Automation Engineer - McKesson - Nashville, TN

(2023-03 - 2023-08)

DMI is the common Platform that supports multiple applications for Healthcare Oncology in McKesson. They maintain data across various domains, including Patients, Pharmacies and Rx Orders. This data undergoes processing through multiple layers for staging, enrichment and optimization.

• Created Automated test cases in various phases of Data Transition from Source to Target during ETL process
• Created a new Integration testing Framework from scratch using Python and Databricks to do the Regression testing for the new deployments through CI/CD. And also can be run as standalone to check the changes in local
• Tested the optimized data streaming pipelines using Azure Event Hubs, ensuring efficient data distribution to multiple downstream systems in real-time, enhancing operational efficiency
• Involved in testing Spark applications using Python to perform various data cleansing, validation, transformation and summarization activities according to the requirement.
• Worked with different data sources like Avro data files, XML files, JSON files, SQL server and Oracle to load data into Hive tables.
• Has good knowledge in Databricks API Testing
• Implemented multiple test cycles while doing data validation