Experience
From neuroscience research to enterprise AI engineering.
Advisory AI Engineer
IBM — Customer Success Engineering
Building enterprise AI systems, multi-agent architectures, and retrieval pipelines — from prototype to production.
- Architected multi-agent orchestration systems with orchestrator and specialist sub-agents
- Built RAG systems with chunking, embeddings, vector retrieval, and grounded generation
- Developed Python tool-calling frameworks for enterprise APIs and workflows
- Built document processing solutions combining vision-language models with PDF extraction tools
- Built evaluation and testing pipelines for agent quality and workflow success
- Authored production deployment of enterprise AI systems and published agents to IBM Agent Catalog
- watsonx
- Orchestrate ADK
- Python
- RAG
- embeddings
- vector databases
- LoRA
- LLM evaluation
- tool calling
- multi-agent systems
AI Engineer
IBM — Client Engineering
Delivering client-facing machine learning, NLP, and generative AI systems for enterprise clients.
- Delivered client-facing generative AI solutions, translating business requirements into production-ready applications
- Built RAG systems with multilingual embedding models and Milvus vector databases
- Developed testing frameworks and evaluation harnesses to validate agent routing logic and model performance
- Led customer-facing architecture and design sessions
- Python
- NLP
- LLMs
- LangChain
- Milvus
- data science
- enterprise architecture
Research Data Scientist
General Dynamics IT — EPA (Federal Contractor)
OCR, NLP, and document intelligence across a large federal document repository.
- Deployed Tesseract OCR across a large document database, automating text extraction from legacy records
- Trained and deployed NLP document classifiers via ensemble learning
- Used transfer learning with RoBERTa and Hugging Face tooling
- Built similarity workflows using transformer embeddings and cosine similarity
- PyTorch
- Hugging Face
- OCR
- Tesseract
- RoBERTa
- NLP
- cosine similarity
Data (Policy) Analyst
State of Washington, Healthcare Authority
Data engineering and policy analysis supporting the audit of Washington's multi-year healthcare expansion.
- Refactored data processing scripts to produce state and federal dataframes used to audit the state's healthcare expansion
- Python
- data processing
- healthcare policy
Senior Data Analyst
Johns Hopkins Health System
Analytics, reporting systems, and healthcare data workflows.
- Produced scheduled and ad-hoc analytical reports for executive leadership
- Built Python and pandas workflows for difficult-to-access datasets
- Redesigned a case management system to accommodate increased patient volume
- Partnered with IT departments and third-party vendors to integrate data sources and streamline reporting pipelines
- Python
- pandas
- analytics
- factor analysis
- reporting systems
Research
Johns Hopkins Medical Institute · NIH (NIDA)
Neuroscience, psychology, and clinical research grounded in data, signals, and behavior.
- Investigated neural mechanisms of motivation and learning using PCA on electrophysiological data and bivariate time-series analysis
- Led startup of a multi-year NIH-funded clinical research study and managed two research interns
- Co-authored 3 peer-reviewed papers, published on PubMed
- statistics
- PCA
- time series analysis
- experimental design
- research methods
- electrophysiology