Aravind Kumar
Atlanta,GA
Summary
Dynamic professional with over 5 years of experience, including 2 years focused on Generative AI and the development of AI-driven solutions using advanced models such as GPT and OpenAI Whisper. Proven expertise in deploying Ollama models for natural language understanding and generation, along with fine-tuning LLaMA 3 for chatbot applications. Demonstrated success in designing healthcare systems that leverage Generative AI models, optimizing AI solutions for business needs, and leading automation projects to enhance testing workflows. A strong background in data center management, QA testing, and data analytics ensures a comprehensive approach to infrastructure optimization and quality assurance across diverse platforms.
Overview
6
6
years of professional experience
Work History
Generative AI Engineer
Informatics Inc.
11.2024 - Current
- The Prior Authorization (PA) project is designed to simplify and automate the traditionally manual and time consuming process of obtaining prior authorization for medical services, medications, or treatments from insurance providers. This process is critical in the healthcare industry to ensure that treatments are medically necessary and covered by the patient’s insurance policy.
- The system leverages cutting-edge AI and machine learning technologies to handle and process both structured data (such as XML) and unstructured data (like free-form text) with high precision. The goal is to streamline communication between healthcare providers, insurance companies, and patients, reducing delays, errors, and administrative burdens.
- Key components of the project include:
- 1. PA Initiation Request: Automates the initial submission of prior authorization requests by extracting and validating relevant patient and treatment details.
- 2. PA Initiation Response: Processes responses from insurance providers, including approvals, denials, or requests for additional information.
- 3. PA Request: Manages end-to-end requests, including tracking and updating the status of ongoing prior authorization submissions.
- 4. PA Response: Provides detailed responses to healthcare providers and patients, enabling them to make timely decisions about treatment options.
- Responsibilities:
- Designed and developed components such as PA Initiation Request, PA Initiation Response, PA Request, and PA Response using C#. Each component automated specific tasks in the prior authorization process, ensuring seamless integration and functionality across the system.
- Integrated GenAI-driven agent components in the Prior Authorization system to streamline insurance workflows.
- Engineered hybrid AI agents capable of understanding and processing both structured XML and unstructured clinical data.
- Deployed Gemma and LLaMA 3 models on AWS EC2 instances, leveraging cloud infrastructure to enable scalable and real-time AI capabilities. These models processed patient and insurance policy data efficiently, automating decision-making and reducing response times.
- Developed and optimized LLM prompts using Postman API calls, refining structured and unstructured queries to improve response accuracy for Prior Authorization models.
- Engineered effective prompts using Postman to guide LLaMA 3 and Gemma models for accurate healthcare query responses from structured and unstructured data.
- Utilized Postman API calls to test and create API requests that aligned with project requirements. Designed and validated appropriate prompts for the AI models, ensuring accurate interpretation and responses to healthcare and insurance-related queries.
- Conducted API-based testing and fine-tuning of LLaMA 3 and Gemma models, enhancing patient and policy data retrieval for real-time insurance decision-making
- Fine-tuned structured and unstructured data (XML) by preprocessing and optimizing them for model performance. This included cleaning and formatting patient information, insurance policy documents, and authorization records for accurate AI-driven outcomes.
- Enabled LLaMA 3 to compare patient and policy data effectively, allowing it to provide precise, real-time answers to insurance agents’ queries, such as determining coverage eligibility, required documentation, or reasons for denial, improving operational efficiency and reducing delays.
Generative AI Engineer
TestGrid.io
11.2023 - 11.2024
- TestGrid CoTester is the world's first AI-powered solution for software testing. It leverages advanced AI algorithms to automate and enhance the testing process, making it more efficient and accurate. CoTester supports a wide range of testing needs, including functional, regression, performance, and security testing across web, mobile, and API platforms. With features like intelligent test generation, automated bug detection, and real-time analytics, CoTester streamlines the testing lifecycle, reduces manual effort, and improves overall software quality.
- Responsibilities:
- Designed, deployed, and maintained intelligent AI agents using LangChain, enabling dynamic user interaction for testing and support platforms.
- Managed end-to-end AI agent lifecycle: scoping requirements, prototyping with LangChain, deploying LLMs, and continuously iterating based on user feedback.
- Led the CoTester project to extract, generate, and automate test cases from web pages using advanced LLMs; improved test coverage and reduced onboarding time for QA teams.
- Trained a custom AI model using Appium and Selenium data to enhance the test automation process, enabling the system to better understand and perform tests based on the specific needs of the TestGrid environment.
- Developed comprehensive test cases from the extracted data, ensuring thorough coverage of all functionalities and test scenarios.
- Implemented an automatic test case generation feature, where CoTester dynamically writes test cases in the programming language requested by the user, improving workflow efficiency and adaptability.
- Led the integration of AI algorithms to automate and enhance the software testing process, reducing manual effort and increasing test accuracy.
- Provided technical support and training to internal teams and customers, ensuring effective use of CoTester.
- Created comprehensive documentation for test processes, AI algorithms, and user guides
- Integrated AI agents into real-world systems including voice interfaces, chatbots, and Streamlit dashboards—automating TestGrid workflows and improving user engagement.
- Leveraged GPT-4 Turbo and Whisper to enable multi-modal Agent interaction (voice and text) and automated redirection to specific TestGrid features.
- Developed and deployed an AI-powered Voice Assistant that integrates Whisper for voice-to-text conversion and ChatGPT-4 Turbo for AI-driven responses, improving user interaction and navigation within the platform.
- For the Voice Assistant, I used GPT-4 for certain clients who were comfortable with processing requests in the cloud, allowing for inbound and outbound calls. For other clients with security concerns, I implemented the Ollama model to run locally, ensuring that there were no external inbound or outbound calls for enhanced security purposes.
- Enabled real-time query handling and automation, allowing users to receive responses and navigate directly to specific product pages like the Real Device Cloud using both voice and text formats.
- Utilized FAISS for Vector Store to optimize the retrieval of relevant information and improve response times within the voice agent
- Delivered Solutions for TestGrid users, allowing seamless interaction with the product through both voice and text commands, providing directions for product usage and answering general queries.
- Implemented and managed vector databases to efficiently store and retrieve high-dimensional data for machine learning applications.
- Developed an interactive Chatbot for TestGrid, utilizing ChatGPT-4 Turbo to provide accurate, real-time responses to user queries about the platform’s features, functionality, and documentation.
QA Testing & Data Center Infrastructure
TestGrid.io
03.2023 - 10.2023
- Designed and implemented automated test scripts using Selenium and Python to enhance the testing process, reducing manual effort and increasing efficiency.
- Provided seamless support to both internal teams and customers, ensuring effective use of the testing product.
- Conducted enterprise-level demos to showcase product capabilities and benefits, driving customer engagement and product adoption.
- Reviewed and validated test cases, ensuring accuracy and coverage of software functionalities through manual and automated testing.
- Experienced in configuring servers and maintaining testing environments to support various testing scenarios.
- Conducted in-depth research on technical issues, providing effective solutions and guiding customers through the resolution process.
- Assisted customers in understanding and utilizing the product, enhancing their overall experience and satisfaction.
- Managed and maintained server infrastructure, ensuring optimal performance and minimizing downtime in a high-availability data center environment.
- Handled server installations, configurations, and upgrades, including the setup of physical and virtual servers to meet business needs.
- Monitored network performance, identifying and troubleshooting connectivity issues with servers, hubs, and other network devices to ensure smooth operations.
- Coordinated hardware maintenance and repair, including replacing faulty components and ensuring all devices were up-to-date and fully operational.
- Implemented and adhered to data center security protocols, safeguarding sensitive data and ensuring compliance with industry standards.
- Environment:
- Languages & Frameworks: Python, Streamlit, FAISS, OpenAI GPT-4 Turbo, Llama3, and Whisper
- Libraries & Tools: OpenAI API, FAISS (for vector store), Whisper (for voice-to-text), Streamlit (for user interface) and RAG
- Hardware: Mac Studio server (for local deployment)
- Platforms: TestGrid platform, FAISS for fast retrieval, Whisper for audio processing
- Operating System: macOS
- Deployment: Local deployment on Mac Studio without internet connection, running models like Mistral and LLaMA 3.1 for offline operation
Laboratory Assistant & Data Center Infrastructure
TestGrid.io
12.2022 - 02.2023
- Managed the testing lab, ensuring the efficient operation and maintenance of lab equipment and mobile devices, including Android and iOS devices.
- Conducted thorough checks on mobile device connections using tools such as multimeters and oscilloscopes to ensure proper functionality and performance.
- Handled backend hardware technology, performing diagnostics and troubleshooting using tools like JTAG debuggers and UART interfaces to resolve issues.
- Maintained an organized lab environment, ensuring all devices and equipment, including testing stations and connectivity tools, were in optimal working condition.
- Collaborated with team members to conduct tests and document results using software such as Excel and TestRail, ensuring accuracy and reliability.
- Implemented best practices for handling and testing mobile devices with tools like ADB (Android Debug Bridge) and Xcode, contributing to the overall quality of lab operations.
- Assisted in the setup and configuration of testing environments for various mobile devices, utilizing mobile device management (MDM) solutions.
- Maintained effective communication with team members and management, contributing to a collaborative and solution-focused environment.
- Gained hands-on experience working in Flexential data center environments, adhering to strict security and operational protocols
- Oversaw the operations of a high-tech testing lab, managing a wide range of mobile devices and ensuring seamless connectivity and functionality across all testing environments.
- Coordinated the integration of backend hardware technology within both the testing lab and data center, ensuring compatibility and efficient performance across systems.
- Streamlined lab and data center workflows, optimizing processes for device testing, data management, and network operations to enhance overall efficiency and reduce downtime.
- Environment:
- Appium, Selenium, Jenkins (CI/CD), PyTest, SQL, BootStrap, TestGrid platform, macOS, iOS, Android, Mac Studio Servers, iOS and Android mobile devices, device hubs, Wi-Fi and wired network configurations, data cables, network hubs, and rack setups in high-availability data center environments.
Business Analyst
Ranbaxy
01.2021 - 06.2022
- As a Business Analyst at Ranbaxy, I played a key role in transforming large volumes of pharmaceutical sales and clinical trial data into actionable insights. My responsibilities included analyzing market trends, sales performance, and drug efficacy, while ensuring compliance with regulatory standards such as FDA and HIPAA. I collaborated with clinical research teams to integrate clinical data with sales performance metrics, improving forecasting and predictive analytics.
- I used advanced SQL, Python, and BI tools like Power BI and Tableau to build interactive dashboards and reports, enabling senior leadership to make informed business decisions. I was involved in data validation, ETL processes, and data governance, ensuring the accuracy and compliance of all data handled across multiple platforms.
- My role also included providing ad-hoc insights to support various departments, including marketing, sales, and clinical research, as well as leading efforts in data integration to ensure seamless reporting and business intelligence.
- Responsibilities:
- Analyzed pharmaceutical sales and distribution data, tracking market trends, sales growth, and product performance to support business intelligence and marketing strategies.
- Performed data profiling, cleaning, and validation on clinical trial data, ensuring compliance with FDA and industry regulations to maintain data accuracy and integrity.
- Built and maintained interactive dashboards in Power BI and Tableau to visualize key performance metrics such as drug performance, sales forecasting, and market penetration.
- Utilized SQL to query large datasets from multiple sources, including sales databases and patient records, to provide comprehensive insights into drug efficacy and market demand.
- Led ETL processes to extract, transform, and load data into a centralized data warehouse, ensuring data accuracy and improving the reporting process.
- Conducted statistical analysis and predictive modeling to forecast drug sales, market performance, and regional trends using historical sales data.
- Collaborated with clinical research teams to integrate clinical trial data with sales performance for advanced analytics and better forecasting models.
- Worked closely with regulatory teams to track compliance data for clinical trials, ensuring all data met FDA and HIPAA guidelines.
- Delivered ad-hoc insights and analysis to senior leadership, aiding in key business decisions for sales growth and product development.
- Performed gap analysis to identify data discrepancies and recommend improvements in sales operations, ensuring accuracy in forecasting and reporting arranged the data governance process
Data Analyst
Sreyas Institute of Engineering and Technology
01.2020 - 12.2020
- As a Part-Time Data Analyst during my bachelor’s program, I supported the administration by managing and analyzing student data, fees, and related academic information. My role involved cleaning and organizing datasets, ensuring accurate fee records, and generating reports to support decision-making and operational efficiency. I utilized Excel for data
- Responsibilities:
- Managed and analyzed student data (enrollment, fees, academic records) using Excel for data tracking, ensuring accurate and organized records.
- Used SQL to query and retrieve data from the student database, providing detailed insights into fee payment and student progress.
- Generated comprehensive financial reports using Excel to track student fee payments, outstanding balances, and academic performance.
- Created and maintained documentation and reports in MS Word, summarizing key findings for the administration and improving decision-making.
- Conducted data cleaning and organization in Excel, ensuring that all student-related data was up to date and accurate.
- Designed dashboards and charts in Excel to present student fee trends and enrollment metrics to the administrative team.
- Collaborated with the administrative team to streamline the fee collection process, using data insights to help optimize workflows.
- Provided periodic reports in MS Word, summarizing enrollment trends, fee collection status, and financial projections.
Education
Master of Science - Information Technology (AI specialization)
Auburn University
Bachelor - Computer Science
Sreyas Institute of Engineering and Technology
Skills
- Operating Systems: Microsoft Windows, macOS, and Ubuntu
- Languages: Python, React JS, Java, JavaScript, C, C
- Python Libraries: PyQt, Pandas, NumPy, SQL Alchemy Python
- Python IDE: Sublime Text 3, VS Code, Jupyter Notebook, PyCharm
- LLM MODELS: GPT3, GPT4
- OPEN LLM: OLLAMA (llama 2 and 3), ChatGPT, Mistral, Stable, Gemma
- Gen AI Frameworks: Lang Chain, Hugging Face, RAG pipeline
- Databases: RDBMS (Oracle, SQL Server, MySQL), No SQL (MongoDB), ASTDB, Excel
- Cloud Services: AWS and Azure
- Design Tools: Power BI, Tableau, JIRA, GNU
- Agile methodology
- TensorFlow framework
- Scikit-learn library
- Machine learning
Timeline
Generative AI Engineer
Informatics Inc.
11.2024 - Current
Generative AI Engineer
TestGrid.io
11.2023 - 11.2024
QA Testing & Data Center Infrastructure
TestGrid.io
03.2023 - 10.2023
Laboratory Assistant & Data Center Infrastructure
TestGrid.io
12.2022 - 02.2023
Business Analyst
Ranbaxy
01.2021 - 06.2022
Data Analyst
Sreyas Institute of Engineering and Technology
01.2020 - 12.2020
Bachelor - Computer Science
Sreyas Institute of Engineering and Technology
Master of Science - Information Technology (AI specialization)
Auburn University
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