Work

• Rondah · Founding AI Engineer

  2025 – Present

  Engineering lead for Rondah's flagship AI Dental Receptionist product, spanning agent harness, backend infrastructure, patient experience, observability, and operational tooling.

  • Drove 10x ARR growth in under a year through product and infrastructure work on the AI receptionist.
  • Owned 0 to 1 expansion into a new clinical vertical, partnering with enterprise DSO leadership to translate workflows into product requirements and ship deployments; ~$1.5M ACV.
  • Built an internal agent platform with deployed MCP servers, custom tools, and system prompts to automate recurring engineering work around triage, configuration, and deployments.
  • Developed observability and LLM-as-Judge infrastructure to monitor agent behavior at scale, automate failure triage, and create a roughly 20% enterprise customer expansion opportunity.
  • Technologies: Google Cloud Suite, Firebase, JavaScript, MCPs, Skills

• Cohere · Software Engineer

  2024 – 2025

  Worked on SWE capability development for frontier models by evaluating code outputs, identifying failure modes, and building verifiable coding evaluations.

  • Led technical evaluation of LLM code outputs, translating model failure modes into targeted problem sets and answer keys.
  • Built a Python + LLM pipeline to extract, normalize, and validate thousands of novel coding problems for automated model assessment.

• BetterUp · Software Engineer

  January 2022 – August 2022

  Worked on expanding BetterUp's in-app content library and automating the metadata pipeline behind content review and recommendation workflows.

  • Grew weekly active user time on-platform by expanding the in-app content library 60% in 2 weeks, mining coach recommendation data in SQL to surface resources users were leaving the app to read.
  • Architected a serverless metadata extraction pipeline using AWS Lambda and Snowflake, reducing manual overhead and enabling automated content updates.
  • Technologies: AWS, Snowflake, Python, SQL, Elasticsearch

• Wish · Machine Learning Engineer

  May 2021 – August 2021

  Strategic product search injection pipeline.

  • Built a multilingual query-to-product matching pipeline to identify the top buyer queries where strategic products could be position-boosted, lifting click-through rate 48% over 2 weeks.
  • Engineered it as a compute-bounded funnel — intent-based length filtering, language detection, and NER entity matching to prune the search space, then SBERT embedding retrieval with cross-encoder reranking — making semantic search over millions of daily queries feasible on limited hardware.
  • Technologies: Snowflake, Apache Airflow & Superset, Hive, Python

• Autodesk · Machine Learning Engineer

  January 2020 – May 2020 // September 2020 – December 2020

  Worked on machine learning and optimization systems for structural design and bridge modeling.

  • Developed a bridge design optimization system using Python and genetic algorithms, achieving roughly 40% automated material reduction while maintaining stress requirements.
  • Technologies: Python, Docker, time series analysis, genetic algorithms

Education

• University of Waterloo
  BASc Mechatronics Engineering
  September 2018 – April 2023 · Distinction
• Georgia Tech
  MS Computer Science
  January 2025 – Paused for Rondah