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# AI Engineer( Austin based)

- **Company:** Autonomize Inc
- **Location:** Austin, TX, United States
- **Experience:** Experienced
- **Contract:** Permanent contract
- **Skills:** LangGraph Framework, Artificial Intelligence, Python (Programming Language), Machine Learning, Open Source Technology, Search Technologies, Pytorch, LangChain, Retrieval-Augmented Generation, Large Language Models, Prompt Engineering, Model Validation, Llamaindex, Kubernetes, Information Technology, HuggingFace, Free and Open-Source Software, Machine Learning Operations, GPT, Docker
- **Published:** October 7, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=841ea603eeef75b0

## About the Role

2+ years experience working in applied 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 working 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 fast.
 * Experience with healthcare, compliance-sensitive data, or regulated environments.
 * A BS/MS in Computer Science, Engineering, Data Science, or a related field, or equivalent experience.

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., Owner mentality. The buck stops with you. You own it, you learn it, and you get it done.
 * Naturally curious. You'd rather experiment than hypothesize. You push boundaries and experiment your way through any problem.
 * Passionate and unafraid. You're committed to the team and the mission.
 * A team player. You love to learn and win together.
 * A strong communicator. You're clear in voice, writing, chat, and video.

## Description

Build production AI pipelines. Own and optimize pipelines that combine LLMs and classical ML (RAG, extraction, scoring, summarization, classification) for utilization management, payment integrity, claims, and appeals.

 * Extract from real-world documents. Implement VLM- and OCR-based pipelines that turn medical documents, faxes, and healthcare forms into structured, reliable data.
 * Fine-tune and adapt models. Run SFT and parameter-efficient (e.g., LoRA) fine-tuning experiments on open-source and proprietary models.
 * Implement retrieval and agents. Build retrieval strategies, prompt chains, tool-using agents, and inference orchestration (e.g., LangGraph) for production use cases.
 * Build evals and analyze errors. Create eval harnesses and test sets, run error analysis, and turn findings into measurable accuracy gains.
 * Monitor and improve. Track and improve model quality, latency, cost, explainability, and safety in production.
 * Experiment fast. Prototype new techniques from recent research and help decide what's ready for production.
 * Collaborate. Work closely with senior MLEs, product, engineering, and domain experts, and document your work clearly.