Aug 2022 – Jun 2025 · 2 yrs 10 mos · Abu Dhabi Emirate, United Arab Emirates · On-site

• Built and launched a scalable health data lake on AWS, unifying multimodal datasets through FHIR standards, and operationalized with Lake Formation, HealthLake, HealthImaging, and HealthOmics to enable next-gen healthcare analytics.
• Built a multi-agent health assistant using fi ne-tuned LLMs across medical specialties, integrated with multimodal health data and a proprietary knowledge base; outperformed foundation models by 38% in accuracy and relevance (internal benchmark).
• Built structured knowledge base powering the LLM solution, aggregating 500K+ scientifi c papers, clinical trials and biobank studies on drug effi cacy, supplements, and lifestyle interventions, enabling physicians and researchers to access insights faster for evidence-based decision-making.
• Designed and delivered a mobile-first healthcare app with a user-centric UI/UX, enabling seamless access to personalized health insights; it showed strong acceptance from initial test users during closed feedback sessions.
• Led the development of secure infrastructure, ensuring end-to-end compliance with HIPAA and GDPR to uphold data privacy and regulatory standards across all platforms.
• Led a cross-functional, globally distributed (US, Poland and India) engineering team of 10+, establishing agile processes, CI/CD workflows, and sprint rituals to drive consistent delivery and high collaboration across time zones.

Nov 2021 – Aug 2022 · 9 mos · Delhi, India

• Served as the Product Owner for the Chegg Content Knowledge Graph, responsible for overseeing a vast network of over 500 million nodes and 2 billion edges.
• Utilized technology strategy to identify and present student journeys tailored to different personas, leveraging recommendation models to enhance user engagement and improve the overall user experience.
• Achieved remarkable results, with an 18% increase in engagement attributed to the implementation of personalized student journeys.
• Collaborated effectively with stakeholders to craft and deliver a comprehensive product roadmap for the Knowledge Graph platform. This roadmap was presented to Chegg's Product and Engineering leadership, outlining the strategic vision for 2022 and beyond.
• Acted as a Scrum Master, leading biweekly sprint grooming, sprint planning, and daily standup meetings with the engineering team. This hands-on approach ensured the efficient execution of the product roadmap and alignment with organizational goals.

Sep 2017 – Feb 2022 · 4 yrs 5 mos · New Delhi, Delhi, India

• Led Product and R&D efforts for Romulus Enterprise's Intelligent Document Intelligence platform for financial services institutions.
• Launched Romulus Equity, a Cloud-based Investment Research platform for intelligent information discovery across a wide range of financial sources, serving buy-side and sell-side customers across the APAC region.
• Interacted with different customers across products for feature interviews, product feedback, and product support.
• Developed product wireframes and design mockups for the products and POC engagements.
• Worked on a state-of-the-art deep learning OCR system, improving Text Detection accuracy by 20% and Text Recognition accuracy by 18% compared to open-source OCR engines.
• Built and scaled code-mixed and code-switched deep learning models to analyze spam and sentiment in Hinglish messages, achieving 95.4% accuracy in spam analysis and 93% accuracy in sentiment analysis across 3 classes.
• Architected and led engineering initiatives of products, from launching MVPs to scaling products in production.
• Conceptualized and developed a low-code web-scraping language that enabled data collection and processing from over 500+ new data sources every day.
• Led a product development team of 15 people, spanning product, engineering, data science, and design, and established engineering processes, including implementing weekly code sprints and conducting code reviews.
• Managed engineering, product, and intern hiring, including sourcing candidates and overseeing the entire hiring process.
• Skills: Python, Machine Learning, Deep Learning, Natural Language Processing, Graph Database (Neo4J), SQL, NoSQL, Business Analytics.

Jun 2016 – Aug 2016 · 2 mos · Noida, Uttar Pradesh, India

• Company Profile: IHS Markit is a leading, global financial information services company with over 10,000 employees. IHS Markit provides information and analysis to support the decision-making process of businesses and governments in industries such as aerospace, defense and security; automotive; chemical; energy; maritime and trade; and technology. The company also provides independent data, valuations and trade processing across all asset classes in order to enhance transparency, reduce risk and improve operational efficiency.
• Key achievements during my internship:
• 1. Developed an interactive dashboard tool for the visualization of the client's profile using R programming
• 2. Analyzed product impact by SWIFT 2016 changes
• 3. Performed inconsistency analysis between different formats of publication mainly ISO 150022 and Proprietary
• 4. Created internal data dictionary for mapping of inbound and outbound fields

Jun 2014 – Jul 2014 · 1 mo · Greater Chennai Area

• Worked on the development of Internal Information Management System of the company. From documentation to development of the application.