Full Stack Engineer with 9+ years in AI Systems & Web Development.
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Full Stack AI Engineer with strong background in Web development, specializing in building production-grade LLM systems that power user-facing products and unlock product scalability. Experienced in designing and deploying agentic AI, retrieval-augmented generation (RAG) pipelines, prompt orchestration systems, and AI-driven automation workflows that reduce operational bottlenecks and enable rapid product iteration. 9+ years of engineering experience spanning AI systems, distributed backend architectures, and cloud-native platforms, with a track record of driving growth in user adoption, request volume, and revenue through applied AI solutions.
Carnegie Mellon University
Bachelor Degree · Computer Science
August 1, 2012 – June 30, 2016
LeyLine AI
Full Stack AI Engineer
May 1, 2024 – April 1, 2026
Seattle, Washington, United States
Birch AI
Full Stack AI Engineer
May 1, 2021 – March 1, 2024
Seattle, Washington, United States
Production Glue
Python Backend Engineer
June 1, 2019 – April 1, 2021
Seattle, Washington, United States
Airbnb
Associate Software Engineer
June 1, 2016 – May 1, 2019
Seattle, Washington, United States
Cultural Fit Analysis
The candidate's diverse experience across different company sizes (Airbnb, Production Glue, Birch AI, LeyLine AI) and domains (web development, search/recommendation, healthcare AI, general LLM platforms) indicates adaptability and a broad perspective. Their focus on building scalable, production-ready AI systems and contributing to engineering standards aligns well with a culture that values innovation, quality, and continuous improvement. The progression from general software engineering to specialized AI roles shows a strong drive for learning and growth.
Soft Skills & Operational Fit
The candidate demonstrates strong problem-solving skills, particularly in addressing complex data challenges for AI systems and optimizing LLM performance. Their experience in fast-scaling startup environments indicates adaptability and a proactive approach to establishing engineering best practices. Collaboration with product, AI research, and creative teams highlights strong cross-functional communication and teamwork. Mentorship experience suggests leadership potential and a commitment to team development.