Resume

Senior AI Engineer specializing in GenAI, retrieval, evaluation, and applied NLP. Strong fit for teams that need someone who can design systems, ship them, and defend technical decisions with evidence.

Years in AI

Core environments

Banking, startups, open source

Flagship OSS projects

Napolab and Hashformers

Building and shipping production GenAI systems for U.S.-based clients.
Designing retrieval, orchestration, and evaluation pipelines for applied AI products.
Collaborating remotely with cross-functional teams on end-to-end AI delivery.

Led development of a product search engine over proprietary data in a founder-led startup.
Reduced RAG indexing time from hours to minutes through data-driven grouping and indexing strategies.
Achieved 90%+ retrieval recall with 20 candidates instead of 100 using redesigned vector retrieval and Gemini augmentation.
Conducted technical interviews and mentored developers.

Built a multi-agent generative AI sales assistant that reduced acquisition cost by 6x.
Improved a production RAG system to cut inference cost by 90% and raise answer quality.
Worked across backend, MLOps, data science, sales, and marketing in a 30M+ customer digital bank.
Developed forecasting and clustering models that improved customer segmentation and campaign targeting.

Built the first production-ready embedding-based annotation methods in the Argilla open-source library.
Translated current NLP research into robust product features and supporting tutorials.

GenAI and Agentic Systems

LLMs RAG Graph RAG Multi-agent systems Tool use Prompt engineering Evaluation

Frameworks and APIs

LangGraph LangChain LlamaIndex OpenAI API Anthropic API AWS Bedrock n8n

ML and Data

Python PyTorch TensorFlow spaCy Hugging Face BigQuery Apache Spark SQL Vector databases

Cloud and Delivery

AWS GCP Azure Docker Kubernetes Kubeflow MLflow FastAPI

Education

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