JEEConf, Kiev, Ukraine

Wednesday, May 15, 2019 | 2 minute read

Ricardo Ferreira

This year I had the honor of speaking at JEEConf; one of the most important Java conferences in Europe hosted in the heart of Ukraine. The conference held two days full of content related to Java and related technologies.

I was really impressed with the number of smart people that I could shake hands and meet at the conference. One of the sessions that I presented there was Tips & Tricks about Apache Kafka in the Cloud for Java Developers, that aimed to show some of the details that developers building Java applications for Apache Kafka should know before venturing themselves in moving their workloads to Cloud.

It was one of the first sessions of the morning, and I was glad to see the room packed with peopled interested in Apache Kafka. Even happier when I found out that 90% of the people there was familiar and/or already working with it.

The slides from this presentation is here:

https://speakerdeck.com/riferrei/tips-and-tricks-about-apache-kafka-in-the-cloud-for-java-developers-e092c220-9869-413d-a55a-a726b6800afd

Of more importantly… the recording of the presentation is also available:

https://www.youtube.com/watch?v=I0Cst1H6edQ

Another talk that I delivered at this conference was Implementing Distributed Tracing ‘Like a Boss’ in your Kafka Deployments ; where I showed how to implemented tracing using the OpenTracing extensions for Kafka, as well as the extensions that I created for KSQL, Connect and REST Proxy.

The slides from this presentation is here:

https://speakerdeck.com/riferrei/implementing-distributed-tracing-like-a-boss-in-your-apache-kafka-deployments

…as well as the recording of the presentation:

https://www.youtube.com/watch?v=9WqdqmQcaro

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© 2018 - 2026 Ricardo Ferreira

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Open Source

I contribute to LangChain4j, an idiomatic open source Java library for building LLM-powered applications on the JVM. Recent work includes adding native vector search embedding stores so developers can build RAG, recommendation engines, and AI memory systems.

I also ported RedisVL to Go, an open source, AI-native client that brings vector search, semantic caching, LLM memory, semantic routing, rerankers, and an MCP server to the Redis ecosystem for Golang developers.

Public Speaking

I’ve been speaking at conferences since 2008 and doing it full time as part of my work with DevRel since 2018. My talks go deep on the systems I build with: distributed systems and event streaming, AI engineering and vector search, and the data infrastructure that has to hold up when the demo ends and production begins. Some of the events I’ve spoken at include AWS re:Invent, Microsoft Ignite, Google Cloud Next, KubeCon, Oracle OpenWorld, QCon, Strange Loop, Kafka Summit, Pulsar Summit, JavaOne, DevNexus, JFokus, JNation, and All Things Open.

Ricardo Ferreira presenting on the main stage at AI DevWorld
On the main stage at AI DevWorld

You can find my upcoming and past talks on my speaking calendar. Recordings also live on my YouTube channel, and the code I write for talks, demos, and workshops is on my GitHub.

Consulting and Professional Services

If you’d like to hire me as a consultant for your projects, speak at your event, or lead a hands-on workshop for your team, contact me at riferrei@riferrei.com. I can understand the scope of your request and provide a free estimate.

Who am I?

I work at the intersection of AI, data infrastructure, and distributed systems, turning complex technology into things developers can understand and products users love.

Lately, that means hands-on AI engineering: building vector search, semantic caching, agent memory, and RAG into the data layer, and figuring out how to make AI agents secure enough to ship. I contribute to open-source projects like LangChain4j and RedisVL for Golang.

The AI-native work isn’t a pivot. It draws on the same systems-design foundation I’ve built for 20+ years: designing data systems for scale, moving data fast, watching where systems break; now applied to vectors and agents. I have worked on RDBMS and Big Data at Oracle; event streaming with Apache Kafka and Apache Flink at Confluent; observability at Elastic; AI and developer tooling at AWS; and NoSQL and vector stores at Redis. That foundation is exactly what separates AI demos that work on stage from AI systems that survive production.

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