Nir Gazit
Director Of Product Management at Trigger.dev
San Francisco, California, United States
Summary
🤩
Rockstar🎓
Top SchoolNir Gazit is a product and engineering leader with eight years of experience building observability and ML-first developer platforms, currently directing Product Management for AI Control Tower at ServiceNow after his startup Traceloop (YC W23) was acquired. He combines startup founder instincts with enterprise-scale architecture expertise from roles as Chief Architect at Fiverr and Tech Lead at Google, focusing on making LLM systems debuggable and reliable in production. A hands-on back-end contributor to open-source projects—most notably an OpenTelemetry-based observability toolkit for LLMs and enhancements to the popular KafkaJS client—he bridges product vision with concrete engineering improvements. Nir’s background spans embedded systems and signal processing in the IDF to R&D leadership in hardware-software products, giving him a rare blend of low-level rigor and cloud-native product strategy. Based in San Francisco, he also advises and angel-invests in developer-focused startups, privileging observability and operational safety in AI.
8 years of coding experience
14 years of employment as a software developer
Y CombinatorMaster’s Degree, Computer Science, Master’s Degree, Computer Science at The Hebrew University of JerusalemB.A, Computer Science, B.A, Computer Science at The Open University of Israel
Hebrew, English, Spanish, German
Github Skills (8)
opentelemetry10
typescript10
kafka10
nodejs10
typescripts10
python10
typescript-types10
testing8
Programming languages (18)
Github contributions (5)
traceloop/openllmetry
Sep 2023 - Apr 2025
Open-source observability for your LLM application, based on OpenTelemetry
Role in this project:
Back-end Developer
Back-end DeveloperContributions:128 releases, 452 reviews, 843 PRs in 1 year 7 months
Contributions summary:Nir primarily contributed to the back-end aspects of the project, focusing on setting up and configuring headers for trace exporting. They fixed bugs related to correctly parsing headers and ensured the correct appending of the /v1/traces endpoint. Furthermore, the user implemented the automatic creation of the dashboard.
artifical-intelligencedatasciencegenerative-aigood-first-issuegood-first-issues
tulios/kafkajs
Dec 2020 - Jan 2021
A modern Apache Kafka client for node.js
Role in this project:Back-end Developer
Back-end DeveloperContributions:9 reviews, 17 commits, 1 PR in 9 days
Contributions summary:Nir focused on implementing and refining the administrative features of the KafkaJS client. Their contributions include enhancing the `fetchConsumerGroupOffsets` functionality to support fetching offsets for multiple topics, optimizing tests, and adding TypeScript types to improve code maintainability. These changes directly impact the library's ability to manage and inspect consumer group states within a Kafka cluster. Further contributions include fixing typos and test flakiness.
apache-kafkakafka-consumernode-jsnpm-packagejavascript
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