Recommendations & agent workflows
Blink
Nov 2025 - Jul 2026AI Engineer
Remote
AI inside an event platform.
Blink is an event-management platform with attendee, session, flight-creation, and hotel-reservation workflows. I worked on recommendation features and their supporting Python services, alongside agent evaluation and document understanding.
Delivered recommendations
Connecting attendees and sessions
The problem was to match attendees and surface relevant sessions inside the event platform. I built content-based filtering capabilities using Python/FastAPI, PostgreSQL, and pgvector, and integrated the recommendation features into a distributed architecture using RabbitMQ.
The delivery included automated tests, CI/CD, and development, staging, and production releases. I collaborated across product and engineering teams. These recommendations were delivered independently of the beta agent. No recommendation uplift, ranking benchmark, or user-count result is recorded.
Beta / feature-flagged
Flight creation through a bounded workflow
I designed and evaluated a LangGraph agent for flight creation within the event-management platform. Five integrated tools covered booking, attendee search, location lookup, and document parsing. The workflow connected AI outputs with backend services and remained behind a feature flag for beta evaluation.
A separate workflow combined optical character recognition (OCR) and multimodal document processing with Docling and Gemini 2.5 Flash to extract structured flight-ticket and hotel data from PDFs and images for platform workflows. This supports document extraction and tool integration experience; it does not establish autonomous ticket purchasing or a general-availability agent release.
Research / evaluation
Measuring the feasibility of local inference
I evaluated Gemma 3 12B served through Ollama on AWS EC2 G5 GPUs. Measurements covered time to first token, token throughput, end-to-end latency, RAM/VRAM, and GPU utilization.
The purpose was to assess self-hosting feasibility. No numeric benchmark, cost saving, production traffic result, or final hosting decision is established by the available record.
Backend contribution
The engineering around the AI
I built and maintained FastAPI services, asynchronous workflows, PostgreSQL-backed APIs, and external-service integrations. I contributed to backend refactoring intended to simplify services and improve multi-tenant support.
Claude Code was part of my engineering workflow for code, tests, documentation, and reports. Architecture work was a contribution alongside colleagues, without a claim of sole ownership or a measured refactoring gain.