Senior AI Engineer: GenAI, RAG & Document QA Architect

Humata; Austin (TX); On-site; USD 140,000 - 190,000; Full time

Job summary

Humata is a seed-stage startup in Austin developing a state-of-the-art GenAI system for document and knowledge-base question-answering. As an AI Engineer, you will prototype and ship new document search methods, including image-based RAG, document understanding, and ML-based re-ranking, while owning key projects and contributing to the cognitive architecture.

You will work in a fast-paced environment, collaborating with a team to push the boundaries of retrieval-augmented generation and

Qualifications

• >5 years of software engineering experience.
• >Hands-on production experience with large language models (LLMs) such as GPT-4 or Llama 3.1.
• >Proven expertise in Retrieval-Augmented Generation (RAG) and tuning for accuracy.
• >Strong knowledge of search engines and information retrieval (ElasticSearch, Vespa).
• >Experience with cloud platforms (AWS, GCP) and SQL databases.
• >Proficiency in Typescript and Python.
• >AI/ML research background with LLM training/fine-tuning.
• >Node.js development experience.
• >Ownership: take initiative and drive projects to completion.
• >Scrappy, action-oriented, fast-paced startup experience.
• >Collaborative team player.

Responsibilities

• Prototype and ship new methods of document search including image-based RAG, document understanding, and ML based re-ranking.
• Take end-to-end ownership of important projects as Humata builds out the cognitive architecture.

Skills

5+ years of software engineering

LLMs (GPT-4, Llama)

RAG (Retrieval-Augmented Generation)

Information retrieval / search

Cloud platforms (AWS, GCP)

SQL databases

Typescript

Python

Node.js

Ownership mentality

Scrappy & action-oriented

Collaborative team player

Tools

ElasticSearch

Vespa

AWS

GCP

SQL databases

Node.js

Typescript

Python

Job description

Humata is a seed-stage startup in Austin developing a state-of-the-art GenAI system for document and knowledge-base question-answering. As an AI Engineer, you will prototype and ship new document search methods, including image-based RAG, document understanding, and ML-based re-ranking, while owning key projects and contributing to the cognitive architecture.

You will work in a fast-paced environment, collaborating with a team to push the boundaries of retrieval-augmented generation and