About Me
I’m Clelia, a DevRel Engineer at Qdrant working on search infrastructure, scaling and performance.
My work sits at the intersection of engineering, open source and technical education: I build OSS projects (with a strong focus on Rust), maintain(ed) widely used AI tooling, and I write and speak publicly about a variety of AI and search-related topics.
I’ve contributed to projects reaching thousands of developers, maintained components of the LlamaIndex ecosystem (including the LlamaParse Platform), written for companies including Google, Render, Auth0 and LanceDB, and created open-source tools adopted by the community.
Writing, Talks & Community
Technical Writing
Articles on coding agents, document workflows and AI infrastructure.
Author of technical articles for LlamaIndex and independently on:
- Coding agent sandboxing
- Skills vs MCP tools
- Observability for AI systems ([1], [2])
- AI agents and the tooling around them ([1], [2])
- Filesystems, search and RAG ([1], [2])
- Vector search performance and infrastructure ([1], [2])
Public Speaking
Talks and YouTube videos around AI and agents.
A selection of contributions:
- Vector search & workflow engineering - Qdrant Vector Space Day (Berlin, Sept. 2025)
- Anatomy of AI agents - Voxel51 Meetup (Stuttgart, April 2026)
- LiteParse: Local Document Parsing for AI Agents
- Build Agents from your Files (with LlamaAgents Builder)
- Qdrant talks & presentations
Community
Building in public.
~5000 LinkedIn followers
900+ X followers
~500 GitHub followers
2.2K+ GitHub stars across projects
Active through blogs, YouTube tutorials, OSS demos and technical talks.
Selected Projects & Open Source
Rust • S3-backed, git-versioned object storage for AI agents • 79 stars
Aggit is git designed for your AI agents.
Add atomic changes, commit them, back them up to a remote S3 server, without never polluting your branch history, and push to GitHub only when you’re satisfied with the result.
Rust • Convert everything to PDF • 249 stars • 20K+ downloads
Package and CLI for converting heterogeneous formats into PDF workflows for GenAI applications.
Adopted by developers building document pipelines.
Rust core • CSV data loader for TypeScript, inspired by Polars and Pandas
Sunbears is a native TypeScript library, cross-compiled from Rust.
Able to read a 1.000.000 lines CSV in 0.3s in Node, SunBears is designed to bear the weight of data-intensive workloads for TypeScript backends.
Rust • Unified interface to OpenAI and Anthropic compatible LLM APIs
Call OpenAI and Anthropic compatible LLM APIs through a single interface, from Rust and other languages.
Rust • Make-like task executor for Unix
A Make-like task executor for Unix operating systems, written in Rust.
Generalist AI agent supporting ACP, MCP and sandboxed execution
Agent framework with support for filesystem tools, memory, TODO tracking, AgentFS and multiple model providers.
Safer coding agents through filesystem sandboxing
Run Claude Code/Codex inside AgentFS rather than real filesystems to reduce destructive operations.
Spotify Wrapped for GitHub
Full-stack Go application with authentication, caching, monitoring and analytics.
Experience
Performance, scalability and infrastructure for search
- Developer Relations focused on performance, scalability and infrastructure for search
- Authored production-ops articles on the Qdrant blog: Memory Tiers in Qdrant (pinned/cached/cold tiers × quantization, benchmark-backed) and Configure Qdrant’s Optimizer for Predictable Search Latency
- Presenting Qdrant talks: qdrant-talks.clelia.dev
Building AI infrastructure and agentic developer tooling
- Working on LlamaAgents and LlamaParse Platform (agent capabilities, knowledge base/agentic retrieval capabilities)
- Maintaining open source projects such as LiteParse and Semtools
- Producing demo for LlamaParse Platform products, also in partnership with other companies such as Google, Render, Qdrant, LanceDB, Auth0
- Producing tech content such as blogs and videos, and engaging with the community at conferences and meetups
LegalForLandlords
AI Engineer
Feb 2025 – May 2025
Legal document understanding with AI
Contributed to pipelines processing legal documents through AI agent orchestration.
Natural History Museum Vienna
Bioinformatics Researcher
Oct 2024 – Mar 2025
Genomics & quantitative biology
Researched human-driven impacts on Drosophila population genetics using genome data.
Criad Ltd
Founding Engineer
Jun 2024 – Feb 2025
AI for architecture & design workflows
Early engineering work around AI-powered products for architects and designers.
Collaborations
Google Developers Blog
Technical Article
https://developers.googleblog.com/build-a-smart-financial-assistant-with-llamaparse-and-gemini-31/
Build a Smart Financial Assistant with LlamaParse and Gemini 3.1
Co-authored technical article on the Google Developers Blog demonstrating how to combine LlamaParse with Gemini 3.1 to build AI-powered document workflows.
Building Document Pipelines That Actually Scale
Contributed a deep-dive on architecting scalable document ingestion pipelines using LlamaParse, covering deployment patterns and performance considerations on Render’s infrastructure.
Securing AI Document Pipelines with LlamaIndex and Auth0
Partnered with Auth0 to write a guide on adding authentication and authorization to AI-powered document workflows, integrating the LlamaParse Platform services with Auth0’s identity platform.
LanceDB
Technical Article
https://www.lancedb.com/blog/smart-parsing-meets-sharp-retrieval-combining-liteparse-and-lancedb
Smart Parsing Meets Sharp Retrieval — Combining LiteParse and LanceDB
Collaborated with the LanceDB team to demonstrate how LiteParse and LanceDB complement each other for efficient multimodal document parsing and vector retrieval at scale.
Education
University of Pavia
BSc Biological Sciences
2022–2025
Genetics • Bioinformatics • Evolution
Biology degree focused on genetics and computational biology.
Dissertation:
“Exploring Potential Commensality Patterns between Drosophila melanogaster and Homo sapiens in Europe”
Supervised by University of Pavia and Natural History Museum Vienna researchers.
A Little More About Me
Beyond my day-to-day engineering work, I try to learn as much as possible through side projects.
My interests increasingly revolve around the database/storage ecosystem (vector DBs, S3), Rust/Go, and platform deployment/orchestration technologies included Docker, Kubernetes and k3s (I am growing my own little cluster!)
I enjoy diving into deep technical topics, researching and understanding code and explaining what I found.
Outside tech: hiking, museums, science, sports and my cats.