Mark Hoy - Enterprise Search - Senior Backend Engineer at Elastic

Mark Hoy

Enterprise Search - Senior Backend Engineer at Elastic

Old Toronto, Ontario, Canada

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Summary

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Rockstar

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Top School

Mark Hoy is a senior backend engineer and enterprise search specialist with nearly three decades of academic and industry experience, currently driving API-first search features and NLP/ML integrations at Elastic. He has deep expertise in information retrieval and text analytics from roles as CTO of Texifter (DiscoverText) and senior architect at Vision Critical, pairing research-grade systems design with production engineering. At Elastic he’s contributed across Kibana and Elasticsearch—implementing Azure OpenAI and Amazon Bedrock inference support and leading a multi-month migration of CI/CD from Jenkins to Buildkite to boost developer productivity. Mark blends hands-on backend, frontend and DevOps work with mentoring and project leadership, and he’s comfortable moving research prototypes into scalable products. Based in Old Toronto, he combines rigorous CMU training with a track record of building search and text-processing infrastructure used in large open-source projects.

4 years of coding experience

22 years of employment as a software developer

Master’s Degree, Information Technology, Master’s Degree, Information Technology at Carnegie Mellon University - H. John Heinz III College

Bachelor’s Degree, Information and Decision Systems, Bachelor’s Degree, Information and Decision Systems at Carnegie Mellon University

Stackoverflow

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Github Skills (32)

javascript10

apidoc10

testing10

amazon-elasticsearch10

metasearch10

kibana10

java10

searching10

javas10

elasticsearchquery10

api10

web-search10

front-end-development10

aws-elasticsearch10

azure-openai10

Programming languages (6)

TypeScriptJavaGoJupyter NotebookRubyPython

Github contributions (5)

elastic/elasticsearch

Aug 2021 - Apr 2025

Free and Open Source, Distributed, RESTful Search Engine

Role in this project:

Back-end Developer

Contributions:121 reviews, 38 PRs, 13 pushes in 3 years 7 months

Contributions summary:Mark implemented and integrated Azure OpenAI Embeddings Inference Service within the Elasticsearch project. Their contributions involved setting up the necessary infrastructure and configurations for interacting with the Azure OpenAI service, including handling API keys, timeouts, and request parameters. The user wrote comprehensive tests for the new service and resolved various linting and style issues. The work culminated in smoke testing and finalizing the Azure OpenAI Embeddings service for the Elasticsearch project.

restfulsearch-engineopensearchelasticsearchjava

elastic/kibana

Mar 2022 - Sep 2022

Your window into the Elastic Stack

Role in this project:

Full-stack Developer

Contributions:70 reviews, 2 commits, 41 PRs in 6 months

Contributions summary:Mark's contributions primarily involve enhancements and modifications to the Kibana platform, particularly within the Enterprise Search and Machine Learning (ML) functionalities. Their work includes removing license requirements for specific features, implementing and testing new API endpoints for ELSER model deployment, and integrating Amazon Bedrock support for inference endpoints. Additionally, the user refactored code related to the display of interface elements in the main search application. These changes span across backend, frontend, and UI components.

elasticdashboardskibanaobservabilitywindow

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