About the role

You’ll work at the intersection of systems design, structured data, and LLM-native intelligence. You

will:

- Build scalable data ingestion pipelines across APIs, scrapers, and third-party sources

- Architect and maintain our real-time knowledge graph of students, firms, and schools

- Lead the migration from Python/Flask to Go (Fiber), with Postgres and Elastic integrations

- Design and prototype AI-native systems - including RAG workflows, OpenAI tooling,

embeddings, and vector search

- Work closely with product/design to turn noisy signals into structured, product-ready insight

- Make architectural decisions that balance performance, velocity, and long-term scale

We're looking for a top 0.1% of engineer who:

- Thrives in fast-paced, high-trust environments and wants to own core systems end-to-end

- Wants to work on complex data + AI problems

- Sees ambiguity as an opportunity to make high-impact decisions

- Values velocity and quality and knows when to optimize for each

Qualifications

- 3 - 8 years of backend engineering experience

- Fluent in Go (or Python/Java/C++ with ability to ramp quickly)

- Experience with large unstructured and structured data sets and real-time ingestion pipelines

- Shipped LLM/AI-powered products (e.g., prompt chains, semantic search, embeddings)

- Strong understanding of Object-Oriented Programming (OOP) principles, software

architecture and scaling distributed systems

- Minimum of a bachelor's degree in Computer Science, Engineering, or a related field

- Bonus: background in NLP/ML or experience building at an early-stage startup