Kacper Łukawski
Lead DevRel at AI Embassy
Krakow, Lesser Poland Voivodeship
Summary
🤩
Rockstar🎓
Top SchoolKacper Łukawski is a Lead DevRel and seasoned AI/ML practitioner with a decade of experience building and advocating for developer-first machine learning and vector search tooling. He currently leads developer relations at deepset (makers of Haystack) and previously scaled developer outreach and integrations at Qdrant, where he contributed backend fixes and added metadata filtering to vector-store integrations used widely in projects like LangChain and the OpenAI Cookbook. As founder of AI Embassy, he champions AI literacy through workshops and community initiatives, blending technical depth with public-facing education. His background spans hands-on data engineering and Spark-based systems to production ML consultancy, giving him a rare combo of low-level systems know-how and API-level developer experience. Based in Krakow, he pairs a strong academic foundation from Jagiellonian University with practical open-source impact on embeddings and vector search workflows. An understated strength is his ability to translate complex backend integrations into clear, reusable examples that accelerate developer adoption.
10 years of coding experience
15 years of employment as a software developer
Magister (Mgr) Informatyka, Magister (Mgr) Informatyka at Jagiellonian University
Polish, English
Stackoverflow
1reputation
0reached
0answers
0questions
Github Skills (12)
openai-api10
vector-database10
embedding10
python10
langchain10
qdrant10
openai9
co9
machine-learning8
testing7
gpt7
chatgpt6
Programming languages (11)
Github contributions (5)
langchain-ai/langchain
Jan 2023 - Mar 2023
🦜🔗 Build context-aware reasoning applications
Role in this project:
Back-end Developer
Back-end DeveloperContributions:11 reviews, 7 commits, 25 PRs in 1 month
Contributions summary:Kacper primarily contributed to the backend functionality of the LangChain project, focusing on vector store integrations and the handling of embeddings. They fixed bugs in the Qdrant vector store integration, including issues with embedding calculations and content retrieval. Furthermore, the user updated the Cohere embedding implementation to ensure data type consistency and added metadata filtering capabilities to the Qdrant vector store.
composability
openai/openai-cookbook
Jan 2023 - Jan 2023
Examples and guides for using the OpenAI API
Role in this project:Back-end Developer
Back-end DeveloperContributions:1 commit, 4 PRs, 5 comments in 1 day
Contributions summary:Kacper contributed significantly to integrating Qdrant, a vector database, into the OpenAI Cookbook. They added examples of how to use Qdrant for embeddings search, including setting up a local Qdrant instance and querying data. They also provided an example of how to use Langchain with Qdrant and OpenAI embeddings. The user's work involved integrating vector databases for efficient similarity searches within the context of OpenAI API usage.
apipythonopenai-apimachine-learningopenai
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