Fleak.ai | Full Stack | REMOTE or onsite (San Jose, California)

About us: we build semantic translation layer for machine generated data streams. The "google translate" for the machine universe to make every device on the planet off the planet AI-ready. If your ambition is not just building another workflow AI agent but bringing AI into the mission critical backbone of our society.

Please apply here: https://amazing-diadem-1ef.notion.site/Full-Stack-Engineer-2...

We've built an app that solves one of the most tedious problems in security engineering - normalizing diverse log formats into a standard schema (OCSF). Security teams typically spend months manually mapping proprietary log formats to work with their tools, costing organizations millions annually in integration costs.

Our approach:

AI-assisted mapping that analyzes your logs and suggests appropriate OCSF mappings Support for both structured JSON logs and unstructured text logs Real-time validation against sample logs as you develop Export portable config files that can run in production with our open-source execution engine

The app is free for the community: https://app.ocsf.fleak.ai/

Break our AI, Win a Chair: We've also launched a challenge with our log classifier AI. Try to stump our classifier with unusual security logs at https://ocsf-classifier.fleak.ai. Winners who successfully "break" our AI will receive a camping chair at our RSAC booth (ESE-65) next week! This helps us improve our models while you test your security knowledge.

We've open-sourced the execution engine (ZephFlow) that powers the production deployments: https://github.com/fleaktech/zephflow-core

Looking for feedback on usability, especially from security engineers who've dealt with log normalization. We're also building a library of templates for common security logs - if you have particular log types that need mapping, we'd love to help create templates for them.

This is gold! practicing this pitch in front of a mirror right now. Agree on the AI part, time has changed....(we figured it was a great buzz word 6 months ago...now not so sure any more) T_T

The common use cases we found so far are two: data tagging see https://docs.fleak.ai/1.0/tutorials/sentiment-labeling and embedding pipeline into vector store, see: https://docs.fleak.ai/1.0/tutorials/pinecone-embedding

Fleak | Fullstack Engineer | Remote (European timezone) |Full time| https://fleak.ai/alpha-test Fleak Explained: A serverless AI workflow builder. Fleak offers a user-friendly visual orchestrator, allowing users to craft their Directed Acyclic Graphs (DAGs) by seamlessly connecting data sources, AI models(GPU/CPU), and user defined functions. With a single click, the visual designs evolve into distributed, high-performance workloads and automated API endpoints. Our core engine stands out with its ability to deploy multi-model real-time workflows without data storage

Our founding team has built Netflix DataMesh, Splunk Core Search, and a quant VC firm with over $1B AUM. We have closed a $1.3M Preseed within 2 months from valley's top infrastructure and cyber security funds. For more details, please apply here: https://amazing-diadem-1ef.notion.site/Full-Stack-Engineer-2...

Fleak (fleak.ai)|Founding Engineer(Java/compilers/distributed systems)|Full-time|Remote/Onsite|San Jose, CA.

Fleak Explained: A compound AI system for real time data streams. Fleak offers a user-friendly visual orchestrator, allowing users to craft their Directed Acyclic Graphs (DAGs) by seamlessly connecting data sources, AI models(GPU/CPU), and user defined functions. With a single click, the visual designs evolve into distributed, high-performance workloads and automated API endpoints. Our core engine stands out with its ability to deploy multi-model real-time data pipelines without a centralized data store over 100 times faster than patching python libraries onto Spark/Flink frameworks.

Our founding team has built Netflix DataMesh, Splunk Core Search, and a quant VC firm with over $1B AUM. We have closed a $1.3M Preseed within 2 months from valley's top infrastructure and cyber security funds. For more details, please apply here: https://amazing-diadem-1ef.notion.site/Founding-Engineer-e34...

Hi! This sounds right up my alley. I have 4 years of experience working on real time streaming (in my case it was CDC replication to a search index). I'm very well versed with data streaming concepts and AWS services, so I'd be happy to apply.

Sounds really interesting! I have ~4 years of experience with java & distributed systems, I'm not really active on github. Can I apply?