AI Developer (Python & AI/ML Specialist)

Role: Lead Generative AI Developer (Python & AI/ML Specialist)
Location: Austin, TX (100% On-site)
Duration: 12 Months (8/11/2026 – 11/11/2026+)
Pay Rate:  $58/hr on W2
W2 Candidates only.

Role Summary
Seeking a 10+ years experienced Lead Generative AI Developer specializing in Python and advanced Artificial Intelligence (AI/ML) frameworks for a 100% on-site role in Austin, TX. 
The ideal candidate will possess deep expertise in building, fine-tuning, and deploying Generative AI models, Large Language Model (LLM) workflows, Retrieval-Augmented Generation (RAG) pipelines, and prompt orchestration using Python. 
Responsibilities center on leading AI software development, integrating machine learning models with big data pipelines, and architecting scalable, enterprise-grade AI applications.

Key Responsibilities
* Generative AI & LLM Engineering: Design, build, and deploy enterprise Generative AI solutions, RAG pipelines, LLM fine-tuning mechanisms, and prompt orchestration frameworks using Python.
* Python Development & Big Data Integration: Write high-performance, modular Python code to build scalable AI microservices, data processing pipelines, and API integrations with enterprise databases and big data platforms.
* AI Model Lifecycle Management: Manage the end-to-end AI/ML model lifecycle, including data preprocessing, feature engineering, model evaluation, guardrails implementation, and observability.
* Technical Leadership & Delivery: Lead technical design discussions, establish best practices for AI software engineering, conduct code reviews, and drive solution delivery across cross-functional teams.
* Architecture & Optimization: Optimize GenAI model performance, latency, and resource utilization while ensuring system scalability, robust security, and compliance.

Required Skills
* Core Technical Stack: 10+ Years Python Development & Software Engineering
* Artificial Intelligence & GenAI: Generative AI, LLM Fine-Tuning, Prompt Engineering, Retrieval-Augmented Generation (RAG), AI Agent Patterns
* AI/ML Libraries & Frameworks: PyTorch, TensorFlow, LangChain, LlamaIndex, Transformers (Hugging Face), OpenAI APIs
* Big Data & APIs: Python for Big Data Processing, RESTful APIs, FastApi/Flask, Microservices Architecture
* SDLC & Engineering Governance: Git, CI/CD, Model Evaluation, Guardrails, AI System Observability, Agile/Scrum

Preferred Qualifications
* AWS Certified Machine Learning – Specialty or Azure AI Engineer Associate certification.
* Exposure to vector databases (Pinecone, Milvus, ChromaDB, Weaviate) and containerized deployment (Docker, Kubernetes).