2023 — Now
New York, New York, United States
● Conceptualized and implemented knowledge-centric agents, abstracting domain data, retrieval, and reasoning so new
use cases could be onboarded without bespoke implementations
● Built an AI evaluation and benchmarking system to generate and manage gold-standard datasets used for k-shot
prompting, testing, and continuous quality improvement
● Designed accuracy measurement workflows using recall and precision metrics to diagnose retrieval and reasoning gaps
and guide system improvements
● Led ingestion and governance of licensed third-party content into internal AI systems via automated, incremental data
pipelines
● Operated as a senior technical lead: contributing production code, defining system architecture, mentoring junior
engineers, and coordinating releases across environments
● Supported re-design and re-architecture of a large AI-assisted research product following user feedback and shifting
requirements
● Extended internal AI platforms to support external client-facing deployments, adapting enterprise-grade systems for
customer delivery
New York, New York, United States
● Designed and delivered LLM-powered AI platforms using retrieval-augmented generation (RAG) and agentic design
patterns to support complex enterprise knowledge workflows
● Built and scaled domain-specific AI agents focused on high-accuracy information retrieval and synthesis, operating
under strict quality and governance requirements
● Improved AI system performance through iterative prompt optimization and evaluation, increasing response accuracy
to 96–99% while significantly reducing inference cost and latency
● Led development of an enterprise AI solution adopted by 500+ internal users, replacing slow, manual
knowledge-request workflows with real-time AI-assisted guidance
● Re-architected legacy, tightly coupled systems into a modular AI platform API, enabling multiple independent agents
to be built and deployed on shared infrastructure
● Validated platform extensibility by enabling additional teams to launch new AI agents with minimal incremental
engineering effort
Nashville, Tennessee, United States
Developed RESTful APIs: Engineered APIs powering million-dollar client-facing products, seamlessly integrating
with microservices architecture. This included backend endpoints, data managers, and access controls, benefiting
diverse client products across the company.
Backend API Migration: Successfully migrated the company's backend API from v1 to enhanced v2 using iDesign methodology, improving scalability by 30% and reducing performance latency by 20%.
Frontend Design and Implementation: Key contributor to UI/UX development, designing and implementing essential frontend components using React. These features boosted customer retention through improved experiences.
RTK Query Integration: Seamlessly integrated APIs with frontend using RTK Query, enhancing data retrieval, updates, and web page performance through effective frontend caching.
Email Automation: Integrated AWS Lambda-powered email automation, enhancing user communication and satisfaction by delivering direct service updates, bypassing manual logins, and improving notifications.
Data Consistency and Connectivity: Identified and resolved backend data issues, ensuring accuracy and compliance across microservices, improving connectivity and addressing previous mapping inconsistencies.
Optimized Data Caching: Revamped production pipelines with Redis cache mechanisms, drastically reducing request processing times and page load speeds.
Enhanced App Server Efficiency: Boosted app server efficiency through BATCH processing, optimizing data handling, interactions with services, and managing extensive data loads.
Code Quality and Testing: Elevated code quality with comprehensive unit testing for frontend and backend components. Introduced new tests and revitalized old ones, enhancing reliability and efficiency.
2020 — 2022
Fort Mill, South Carolina, United States
Monetized Widgets Migration: Led a 3-person team for end-to-end monetized widgets migration across site portfolio, encompassing validation, seamless component integration, and impactful frontend enhancements. Replaced third-party software with internal widgets, reducing redundancy and increasing cost efficiency.
Components Empowerment: Developed diverse components and templates with meticulous documentation, empowering publishers to enhance content creation efficiency, resulting in amplified website visits and increased ad revenue.
Lead Generation Enhancement: Strategically integrated tracking into pivotal components like 'call to actions,' amplifying lead generation insights. Collected per-component data using an internal tool for thorough expert analysis. Data-driven approach informed robust A/B testing, optimizing leads and user experiences for heightened website traffic and ad revenue.
JamStack to WordPress Transition: Led site re-architecture, transitioning 'JamStack website' to WordPress with proprietary web components. Collaborated cross-functionally with designers, publishing, and product owners. Result: enhanced A/B testing, tracking, and ad revenue on WordPress sites. Mentored junior engineers for project success.
Package Version Management: Authored documentation for efficient package version updates, preventing CI/CD workflow failures due to outdated or insecure dependencies.
Machine Learning Integration: Integrated ML API into article recommendation section, significantly improving recommended articles by dynamically curating content based on readers' behavior and searched school programs.
Chapel Hill, North Carolina, United States
Designed UI and constructed Angular-based web applications: Developed a user-friendly interface that enabled cancer researchers at UNC Lineberger Comprehensive Cancer Center to upload CSV files and input specific genetic patterns. The application efficiently traversed substantial datasets using regex, generating lists of relevant genetic strings that matched the specified patterns. This streamlined data extraction and facilitated advanced research analysis.
Enhanced data processing with Python: Developed a Python program for the targeted extraction of pertinent information from extensive CSV files. This enabled cancer researchers to effectively filter and analyze their data. The code, executed through the terminal, streamlined data extraction for research purposes.
Education
2017 — 2020
The University of North Carolina at Chapel Hill
Bachelor's degree
2017 — 2020