AI Engineer

Autonomize AI is building category-defining AI products that deliver real-world impact in healthcare. This onsite role in Austin, TX brings research to production fast, with significant ownership, modern infrastructure, and a team that values experimentation and clear execution.

As an AI Engineer, you will help build and optimize production AI systems for healthcare agents and copilots, spanning LLM/VLM/RAG and classical ML, document extraction, fine-tuning, evaluation, monitoring, and fast iteration from new ideas to shipped capability.

What you’ll do

• Build and own production AI pipelines that combine LLMs and classical ML, including RAG, extraction, scoring, summarization, and classification for utilization management, payment integrity, claims, and appeals.
• Implement VLM- and OCR-based pipelines to convert medical documents, faxes, and healthcare forms into structured, reliable data.
• Run SFT and parameter-efficient fine-tuning (for example LoRA) on both open-source and proprietary models.
• Create retrieval strategies, prompt chains, tool-using agents, and production inference orchestration (for example LangGraph).
• Build evaluation harnesses and test sets, perform error analysis, and translate findings into measurable accuracy improvements.
• Track and improve model quality, latency, cost, explainability, and safety in production.
• Prototype techniques from recent research and help determine what is ready for production adoption.
• Collaborate with senior MLEs, product, engineering, and domain experts, and document work clearly.

What you bring

• 2+ years of experience applying ML and LLMs.
• Strong Python skills and familiarity with PyTorch, Hugging Face Transformers, and LLM frameworks (LangChain, LangGraph, LlamaIndex).
• Comfort with embeddings, vector search, retrieval pipelines, and prompt engineering.
• Experience fine-tuning or adapting models, plus knowledge of classical ML and NLP.
• Understanding of model evaluation, observability, and responsible AI practices.
• Experience deploying models to production and familiarity with MLOps tooling (MLflow, Docker, Kubernetes).
• Solid software engineering fundamentals and clean, testable code.
• A bias for experimentation, clarity, and shipping quickly.
• Experience with healthcare, compliance-sensitive data, or regulated environments.
• BS/MS in Computer Science, Engineering, Data Science, or related field, or equivalent experience.

Technologies you’ll work with

Python, PyTorch, Hugging Face Transformers, LangChain, LangGraph, LlamaIndex, embeddings, vector search, SFT, LoRA, MLflow, Docker, Kubernetes

Benefits

• Real-world impact through category-defining AI products
• Hard, unsolved ML problems
• Fast research to production
• Significant ownership and autonomy
• Modern stack and compute
• Build your public profile
• Learn with strong peers
• High-growth environment with exceptional technical challenges
• Competitive compensation with performance incentives
• 100% employer-paid health, vision, and dental insurance
• Retirement plans (401k), disability insurance, and employee assistance programs

Nice to have

• Experience with VLMs or document AI
• Exposure to healthcare payer workflows (UM, claims, prior authorization, medical coding)
• Experience with agent frameworks or multi-step reasoning systems
• Open-source contributions, side projects, or technical writing

How you show up

• Owner mentality: you take responsibility, learn continuously, and drive work to completion.
• Curiosity: you prefer experimenting over guessing and push boundaries to solve problems.
• Team commitment: you’re passionate about the mission and committed to the team.
• Collaboration: you enjoy learning and winning together.
• Clear communication: you can explain work in writing, chat, and video.