Pre-screened and vetted in New York.
Junior AI/ML Engineer specializing in LLMs, RAG, and document intelligence
Junior Technology Strategy Consultant specializing in cloud and enterprise transformation
Junior Software Engineer specializing in backend systems and AI/ML
“Built a RAG-based AI research copilot for technical documents, implementing a Next.js/TypeScript frontend with route-based organization (/, /chat, /settings) and an API-driven thin-client approach; product has been used with a lightweight frontend and is being iterated toward a fuller release. Also designed and optimized Postgres schemas and queries for biological dataset analytics at a seed-stage startup, emphasizing pragmatic speed/quality tradeoffs and end-to-end ownership.”
Senior Full-Stack Engineer specializing in LLM applications and cloud-native systems
Senior Backend Developer specializing in AWS-native Python systems and data workflows
Intern Software Engineer specializing in ML applications and LLM platform engineering
“Full-stack engineer who builds and scales customer-facing and internal AI products end-to-end (React/TypeScript/FastAPI/MongoDB) with strong product instrumentation and rapid MVP iteration. Built an AI-powered code review assistant adopted across teams and integrated into CI/CD, reducing manual review time by 30%+, and has hands-on experience with LLM retrieval/reasoning systems (LangChain + FAISS) and microservices scaling using RabbitMQ, Docker, and AWS.”
Junior Backend Software Engineer specializing in search, data systems, and LLM applications
“Built a contract and customer documentation retrieval solution for Urban Studio, designing a RAG + Elasticsearch hybrid search stack (RRF + cross-encoder reranking) with a strong emphasis on chunking/data quality and hallucination reduction. Experienced in diagnosing LLM workflow issues via observability traces and tailoring technical demos to developer concerns like reliability and high concurrency.”
Junior Backend Software Engineer specializing in Java Spring Boot and PHP Laravel
“Built and shipped a production LLM-powered document processing agent (ingestion→OCR→LLM extraction/classification→validation→DB/workflow triggers) using Kafka and PostgreSQL. Emphasizes production reliability with strict JSON schemas, idempotent services, retries/backoff, fallback models, and human-in-the-loop review—driving ~90% automation, minutes-to-seconds processing, and ~10x throughput.”