Bachelor of Science, Computer Science & Mathematics
About
I am a software engineer in New York. Most of my work sits at the seam between AI research and the systems that have to run it.
Biography
I work at FTAI Aviation in New York, where I build the retrieval and agent infrastructure behind customer-facing AI features. That means a RAG backend in Python and FastAPI, multi-tenant agentic workflows exposed over Model Context Protocol servers, and the Azure DevOps pipelines that get all of it onto Kubernetes without drama.
Before that I spent two years in computer vision research at Washington University in St. Louis, across the Multimodal AI Lab and the Digital Innovation Accelerator, with a parallel stint at SLU’s Multimodal AI Lab. I have contributed to work on satellite image synthesis and cross-view pose estimation, and I led computer vision for WashU’s Ursaworks robotics team, which is where I learned what a latency budget feels like when it is set by physics rather than by an SLO.
The thread running through all of it is the same problem from different angles: research code demonstrates that something is possible, and then somebody has to make it dependable. I have mostly been that second person, and I have come to like it.
Skills
Emphasised entries are the ones I use in production most weeks. There are no proficiency bars here, because a bar implies a measurement nobody took.
Languages
Python and SQL daily at FTAI. Rust and C++ on systems and infrastructure work.
- Python
- SQL
- TypeScript / JavaScript
- Rust
- C++
- Node.js
- HTML / CSS
Backend and APIs
The service layer for every AI system I have shipped.
- FastAPI
- REST APIs
- OAuth2
- Server-sent events
- React
- Next.js
- Gradio
AI and machine learning
Production retrieval and agent systems at FTAI; model training in research settings.
- RAG
- LangChain
- Agentic systems
- Model Context Protocol
- PyTorch
- Model evaluation and benchmarking
- ONNX
- TensorRT
- FAISS
- OpenAI / LLM APIs
Data and storage
Postgres and Redis are the pair I reach for most; the rest come out for scale.
- PostgreSQL
- Redis
- Apache Spark
- Apache Kafka
- BigQuery
Infrastructure and delivery
Containerised services on Kubernetes, shipped through Azure DevOps pipelines.
- Linux
- Docker
- Kubernetes
- Azure DevOps
- CI/CD
- Observability and logging
- Terraform
- GitLab CI
- AWS
- Microsoft Azure
- GCP
- HPC Slurm
Testing and tooling
Automated coverage is the reason the release pipeline is allowed to be fast.
- pytest
- Automated testing
- Git
- ruff / mypy
- Prometheus
- Postman
- CMake
- Bazel
Education
Press
Students in summer program develop AI tools, advance faculty research
Coverage of the Digital Transformation Summer Corps, including the vision-language system my team built for assessing neighbourhood walkability, greenery and safety. I described the combination of street-view imagery and language models as a way to “speak” with a city.
Personal
Outside of work I play board games, travel when I can, and play basketball. I used to volunteer as an EMT for my local town, which is still the most direct reminder I have that competence under pressure matters more than looking busy.