Sam Doran Email & Phone Number

New York, Ny, Us

Promoted in 1 year to SE II for database / Kubernetes expertise and “exceptional” review for ambition. Designed system architecture and co-led MariaDB Kubernetes migration (11 billion monthly queries). Created diagrams, coordinated with teams, and made sprint maps. Migration completes move to k8s, saving $20 million/year.Replaced MariaDB’s load balancer (HAProxy) with Kubernetes services, reducing architecture from 7 to 6 components.Upgraded Appian’s Elasticsearch-based search infrastructure. Investigated vector search capabilities. Established baseline performance of vector, BM25, and RRF search. Enabled vector search for 5 AI/ML teams, saving $500,000.Prototyped Retrieval-Augmented Generation (RAG) system using Elasticsearch, which informed product roadmap.

Updated JDBC based integration’s UI to account for driver specific issues, enabling tailored UI interactions for Databricks, Snowflake, SAP HANA, and Denodo.Improved hotfix utility scripts to reduce hotfix release time by 400% and eliminate the possibility of user errors. Connected MariaDB to Prometheus and Grafana, enabling real-time metrics tracking and visualization.

Created custom testing framework for data objects stored on the Appian platform. Used framework to write tests increasing the number of performance tests by 100%.

Implemented checkbox detection and state extraction using OpenCV. Tested key metrics such as precision and recall. Increased detection accuracy by 15%. Reduced dependency on AWS, letting customers use OCR within Appian. Developed tooling on top of Data Version Control (DVC), allowing customers to upload and track their training data.

Cambridge, Massachusetts, United States

Built autonomous agents using expert systems in Unity based military training simulation. Training simulation generated training data and laid groundwork for reinforcement learning.

Developed web-mapping application used in study of map interaction modality used by 30 people in year-long study.