Principal engineer driving agent orchestration and AI tooling at Microsoft
Drives AI agent learning resources and orchestration protocol work at Microsoft. Lands changes in a2aproject/A2A, a protocol for communication between agentic applications.
CRM data is slow and reactive. GitHub is fast: see what your technical targets are working on right now, where they live and what they are about to build.
Engineers at target accounts building agents
Principal engineer driving agent orchestration and AI tooling at Microsoft
Drives AI agent learning resources and orchestration protocol work at Microsoft. Lands changes in a2aproject/A2A, a protocol for communication between agentic applications.
CRACKED
Active 5 days ago
Seoul, South Korea
Drives AI agent learning resources and orchestration protocol work at Microsoft. Lands changes in a2aproject/A2A, a protocol for communication between agentic applications.
4,269 contributions this year
Sr. engineer at AWS building production agent SDKs
Delivers agent SDKs at Amazon Web Services. Contributes to strands-agents/harness-sdk, a software development kit for building AI agents, and strands-agents/tools, a set of tools for agents.
CRACKED
Active 2 days ago
New Jersey, United States
Delivers agent SDKs at Amazon Web Services. Contributes to strands-agents/harness-sdk, a software development kit for building AI agents, and strands-agents/tools, a set of tools for agents.
3,374 contributions this year
Go and TypeScript Staff engineer bridging infrastructure and AI agents at Google
Ships AI agent tooling in TypeScript at Google, after software engineering at Meta. Contributes to Netflix/rend, a memcached proxy for managing data caches.
CRACKED
Active 6 days ago
Sunnyvale, United States
Ships AI agent tooling in TypeScript at Google, after software engineering at Meta. Contributes to Netflix/rend, a memcached proxy for managing data caches.
949 contributions this year
For founders, product, data and partnerships teams.
Step 1
Pass contacts or accounts over the API: a name and company, a LinkedIn or a GitHub.
Step 2
Each person matched across GitHub and LinkedIn, with what they build, their languages and a ranked score.
Step 3
Show it on every record, let customers filter by what people build, and keep it fresh as they ship and move.
Run it in Claude, or build on the API. See how Vamo compares with people data APIs.
© 2026 Vamo Holdings, Inc.