Jeff Lingad

• Architected and implemented a microservices-based banking application using Python, FastAPI, and React, resulting in a 40% improvement in transaction processing speed and 99.99% system availability for a major financial client.
• Developed asynchronous Python services using Tornado framework for real-time transaction processing, handling 5000+ concurrent connections with sub-50ms response times.
• Built and maintained Python-based data processing pipelines using asynchronous programming patterns, enabling real-time data analysis for fraud detection.
• Created MongoDB aggregation pipelines for complex financial reporting, reducing report generation time from hours to minutes while handling terabytes of transaction data.
• Designed RESTful API contracts following OpenAPI specifications, enabling seamless integration between frontend and backend services while reducing development time by 35%.
• Spearheaded the migration of legacy systems to AWS cloud infrastructure, leveraging Docker and Kubernetes for containerization, which reduced operational costs by 35% and improved scalability. 
• Developed a secure authentication and authorization system using Nest.js and TypeScript, implementing role-based access control that reduced security vulnerabilities by 85% and improved API response times by 45%. 
• Designed and developed RESTful APIs and GraphQL endpoints using Python and Django for the TCS Bank’s financial platform, enabling seamless integration with third-party services and improving data retrieval efficiency by 50%. 
• Implemented CI/CD pipelines using Jenkins and GitLab CI, automating the deployment process and reducing release cycles from weeks to days while maintaining code quality through automated testing. 
• Led a team of 8 developers in the development of a machine learning-powered fraud detection system using TensorFlow and Python, which identified potentially fraudulent transactions with 95% accuracy. 
• Developed high-performance microservices using Go for critical financial transaction processing, achieving 3x throughput improvement and 70% reduction in latency compared to previous implementations. 
• Optimized database performance by redesigning schema and implementing query optimization techniques for PostgreSQL and MongoDB, resulting in a 60% reduction in query response time. 
• Developed real-time data processing pipelines using Kafka and ELK Stack for the TCS Intelligent Urban Exchange platform, enabling smart city clients to process over 1 million events per second. 
• Architected and implemented a blockchain-based supply chain traceability solution using Hyperledger Fabric, enabling end-to-end product tracking that improved transparency by 90% and reduced fraud incidents by 75%. 
• Implemented infrastructure as code using Terraform and Ansible, reducing environment setup time by 75% and ensuring consistency across development, testing, and production environments. 
• Implemented comprehensive test automation framework using Pytest and Selenium, achieving 90% test coverage and reducing regression testing time by 70% while improving software quality. 
• Created responsive and accessible front-end interfaces using Angular and Material UI, improving user experience and achieving WCAG 2.1 AA compliance for government clients. 
• Integrated AI-powered chatbot functionality using Natural Language Processing and Azure Cognitive Services, reducing customer support inquiries by 30% for a retail banking client. 
• Engineered and optimized Linux-based server environments for high-performance computing applications, resulting in a 55% reduction in processing time and 40% decrease in infrastructure costs. 
• Conducted advanced statistical analysis and predictive modeling using R and Python with pandas for financial risk assessment, improving risk prediction accuracy by 42% and reducing false positives by 65%. 
• Engineered high-availability cloud architecture on Azure with auto-scaling capabilities, achieving 99.99% uptime for mission-critical applications handling over 10,000 concurrent users. 
• Implemented comprehensive monitoring and alerting solutions using Prometheus and Grafana, reducing system downtime by 70% through proactive issue detection and resolution. 
• Developed data analytics solutions using Spark and Hadoop for the TCS ADD platform, enabling pharmaceutical clients to process clinical trial data 3x faster than previous methods. 
• Mentored junior developers on Python best practices, test-driven development, and cloud technologies, resulting in a 40% increase in team productivity and knowledge sharing.

• Led the redesign of Visme's data visualization components using React, Vue, D3.js and SVG, resulting in a 35% improvement in rendering performance and enabling users to create complex interactive charts with 50% less effort. 
• Built Python Flask backend services to support the visualization platform, developing RESTful APIs that handled 2M+ daily requests with 99.9% uptime.
• Implemented asynchronous data processing using Python Tornado to handle real-time chart updates, reducing rendering latency by 60%.
• Architected MongoDB database schemas optimized for visualization data, implementing efficient indexing strategies that improved query performance by 75%.
• Architected and implemented a real-time collaboration feature using WebSockets and Redux, allowing multiple users to simultaneously edit design projects and increasing team productivity by 40%. 
• Optimized front-end performance by implementing code splitting and lazy loading in React, reducing initial load time by 60% and improving user retention rates by 25%. 
• Developed a custom design system library with reusable UI components using TypeScript and Storybook, streamlining the development process and ensuring consistent user experience across the platform. 
• Integrated AWS S3 and CloudFront CDN for asset management and delivery, reducing image and video loading times by 70% and supporting the platform's growth to over 18 million users. 
• Implemented AI-powered design suggestion features using TensorFlow.js and computer vision algorithms, which increased user design quality scores by 45% and reduced template selection time by 30%. 
• Established end-to-end testing infrastructure using Cypress and Jest, reducing critical bugs in production by 85% and improving release confidence across the development team. 
• Developed data visualization algorithms using R and Python libraries to generate advanced statistical charts, increasing the variety of available visualization options by 200% and enhancing user engagement. 
• Designed and implemented NFT creation and minting functionality for digital assets, enabling users to tokenize their designs on Ethereum and Polygon networks, resulting in a new revenue stream that grew by 120% in the first quarter. 
• Mentored a team of 5 developers on modern front-end practices and design principles, implementing code reviews and pair programming sessions that improved code quality metrics by 45%. 

• Developed robust Python microservices using Flask and Tornado frameworks for Twitter's notification delivery system, handling 10M+ daily requests with sub-50ms response times.
• Designed and implemented RESTful APIs following industry best practices for Twitter's developer platform, enabling seamless integration with third-party applications.
• Built high-performance MongoDB aggregation pipelines for real-time analytics, processing terabytes of engagement data with optimized queries.
• Implemented asynchronous processing patterns in Python to handle concurrent webhook deliveries, improving throughput by 300% compared to synchronous implementations.
• Developed and optimized backend services for Twitter's real-time notification system using Scala and Java, reducing latency by 40% and supporting over 500 million daily notifications. 
• Implemented distributed data processing pipelines with Kafka and Spark, enabling real-time analytics on tweet engagement metrics that processed over 6,000 events per second. 
• Built and maintained scalable microservices using Nest.js and TypeScript for Twitter's internal developer tools, which improved development workflow efficiency by 55% and reduced API integration time by 40%. 
• Developed high-throughput microservices using Go for Twitter's URL shortening service, handling over 1 billion requests per day with 99.999% availability and sub-millisecond response times. 
• Architected and built a recommendation engine using machine learning algorithms and NLP, increasing user engagement with suggested content by 28% and time spent on platform by 15%. 
• Led the migration of critical microservices from monolithic architecture to Kubernetes, improving deployment frequency from bi-weekly to daily and reducing system downtime by 75%. 
• Developed and maintained Linux-based automation scripts using Bash and Python for system administration tasks, reducing operational overhead by 65% and improving deployment reliability. 
• Designed and implemented NFT creation and minting functionality for digital assets, enabling users to tokenize their designs on Ethereum and Polygon networks, resulting in a new revenue stream that grew by 120% in the first quarter. 
• Designed and implemented fault-tolerant, high-availability systems using Redis and Cassandra, achieving 99.99% uptime for core user-facing features during peak traffic events. 
• Collaborated with cross-functional teams to develop GraphQL APIs that reduced frontend-backend data transfer by 60% and improved mobile app performance. 
• Developed and maintained comprehensive test suites using Jest and Mocha for frontend components and API endpoints, achieving 95% code coverage and reducing production incidents by 65%. 
• Prototyped a decentralized identity verification system using Ethereum smart contracts, enabling secure and privacy-preserving user authentication that reduced fake account creation by 60%. 
• Engineered performance monitoring solutions using custom metrics and observability tools, identifying and resolving bottlenecks that improved overall system throughput by 35%. 
• Implemented security enhancements and OAuth authentication protocols that strengthened platform integrity and reduced unauthorized access attempts by 90%. 
• Mentored junior engineers through code reviews and pair programming sessions, helping to reduce onboarding time by 30% and improving team code quality metrics.

• Developed backend services using Python Django and Flask for e-commerce applications, implementing RESTful APIs that processed 1M+ daily transactions.
• Created asynchronous processing systems using Python Tornado for order fulfillment workflows, improving order processing speed by 65%.
• Implemented MongoDB databases for product catalogs and customer data, optimizing query performance and enabling real-time inventory updates.
• Developed and maintained over 30 responsive websites using PHP, Laravel, HTML5, and CSS3, resulting in a 45% increase in client satisfaction and 25% growth in repeat business. 
• Designed and developed enterprise web applications using C# and ASP.NET MVC for government clients, resulting in 70% improvement in process efficiency and 50% reduction in paperwork. 
• Implemented custom e-commerce solutions with Magento and WooCommerce, increasing online sales by an average of 60% for retail clients and reducing cart abandonment by 35%. 
• Designed and optimized MySQL database schemas and queries, improving website loading speeds by 50% and enhancing overall user experience. 
• Integrated third-party APIs for payment processing, shipping, and social media platforms, expanding functionality and increasing conversion rates by 40% across client websites. 
• Led SEO optimization initiatives that improved organic search rankings, resulting in a 150% increase in traffic and 85% improvement in search engine visibility for client websites.

Computer Science, GPA 3.7/4