Skills

Backend Engineer · AI Systems

What I do

I make AI models work reliably in production. That means the unglamorous parts — queues that survive worker crashes, idempotent jobs, schemas that hold up under load — built around inference pipelines that actually ship. Backend by trade, AI systems by specialty.

Core stack
  • TypeScript / Node.js (NestJS, Express)
  • Python (FastAPI)
  • PostgreSQL · Redis & BullMQ
Also fluent in
  • React / Next.js, React Native (Expo)
  • Firebase / Firestore, Google Cloud Platform

Get in Touch

Backend & Distributed Systems

I design and build backend systems that stay correct under failure — REST APIs, microservices, and queue-based architectures with Redis and BullMQ.

  • API Design (Node.js / NestJS, FastAPI)
  • Queues, Streaming & Batch Processing
  • Idempotent Job Design

AI Systems in Production

I take AI models from "works in a notebook" to production — batch inference pipelines processing 1,000+ images per run, structured LLM outputs, and vector search.

  • Batch Inference Pipelines
  • Claude API & Structured Outputs
  • Embeddings & Vector Search (pgvector)

Data & PostgreSQL

Data modelling is where systems live or die. I work in PostgreSQL at the level of query plans, not just queries — plus Firestore and BigQuery where they fit.

  • Schema Design & Indexing
  • Row-Level Security & pgvector
  • Firebase/Firestore · BigQuery

Cloud & DevOps

I ship and operate what I build — from containerised services to CI/CD pipelines, across Google Cloud Platform and AWS.

  • GCP · AWS (EC2, S3, RDS, Lambda)
  • Docker & CI/CD
  • Linux & Production Operations
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