Nov 2024 – Present · 1 yr 7 mos · Reston, Virginia, United States · Remote

• Drove core enhancements to AI infrastructure and data pipelines that directly improved LLM-driven chat summarization accuracy by 35% and reduced medical information loss by 25%, aligning closely with product reliability goals in healthcare use cases. Delivered high-precision chat restoration capabilities with high recovery rate, lowering support volume by 20% and improving user trust.
• Co-developed a dynamic prompt enhancement engine that enriched LLM input with curated insights from unstructured sources, increasing response precision by 30% and improving knowledge coverage. Architected a configurable retry framework with exponential backoff and intelligent error handling, boosting system resilience and reducing transient API failures by 40%.
• Established robust code quality practices by integrating the Ruff linter at scale, leading to an 85% drop in lint violations and earlier defect detection. These initiatives improved both platform stability and engineering velocity across the team.