Python + Gen AI Developer - Dallas, TX

Role Summary

We are seeking a Generative AI Engineer to build, optimize, and scale production-ready AI applications. You will design complex multi-agent systems, implement advanced RAG pipelines, and manage the deployment of both frontier and local LLMs. The ideal candidate blends deep machine learning expertise with modern software engineering practices.

Technical Stack

LLMs

Gemini, OpenAI, Claude, Llama, and Local Model deployment.

Frameworks

LangChain, LlamaIndex, and Hugging Face.

Orchestration

LangGraph and Multi-Agent Systems (MAS).

Development

Python, FastAPI, and Asynchronous Programming.

RAG & Data

PostgreSQL, Vector Databases, and Advanced Retrieval strategies.

ML/DL

PyTorch, TensorFlow, and Model Fine-tuning.

Deployment

Docker, Production API management, and LLM monitoring.

Tools

Prompt Engineering, Workflow Design, and GenAI Optimization.

Key Responsibilities

Develop and orchestrate sophisticated AI workflows using LangGraph and multi-agent architectures.

Build and maintain Advanced RAG systems utilizing LlamaIndex and vector databases for high-accuracy retrieval.

Integrate and swap diverse LLMs (commercial and open-source) based on performance and cost requirements.

Design and deploy high-performance, scalable backend services using FastAPI and Async Python.

Fine-tune large language models (LLMs) using PyTorch/TensorFlow to improve domain-specific performance.

Optimize GenAI workflows for latency, cost, and reliability using advanced prompt engineering and monitoring tools.

Containerize and deploy AI services via Docker to production environments.

Required Qualifications

7+ years of hands-on experience building and deploying GenAI applications in a production setting.

Strong proficiency in Python and the modern AI library ecosystem (LangChain, LlamaIndex, etc.).

Experience with vector search, embedding models, and advanced data retrieval patterns.

Knowledge of model fine-tuning techniques and local LLM quantization/hosting.

Familiarity with production-grade monitoring, API security, and CI/CD for ML.