Python + AI Lead | Dallas, Texas

Stellent IT LLC; Dallas (TX); On-site; USD 180,000 - 240,000; Full time

Job summary

Stellent IT LLC in Dallas, TX seeks a Python + AI Lead to architect and deliver production AI/ML systems. You will own the full lifecycle from data engineering to deployment, build scalable RESTful services with Python frameworks like FastAPI/Flask, and drive MLOps practices in a cloud environment.

You will collaborate with data science and product teams, implement prompt engineering, RAG, and integrate major LLM APIs, while maintaining robust CI/CD and containerization with Docker on

Qualifications

• 10+ years of total software engineering experience.
• 5+ years of hands-on Python development.
• Delivery of at least one production AI/ML or LLM-powered system.
• Understanding of the AI Development Life Cycle (data engineering, experimentation, deployment, monitoring).
• Experience with prompt engineering, Retrieval-Augmented Generation (RAG), and major LLM APIs.
• RESTful APIs, Docker, and deploying backend systems on AWS, GCP, or Azure.
• Git and CI/CD release workflows.
• Clear technical communication across engineering, data science, and product teams.

Skills

Overall Experience

Production AI Delivery

AIDLC Proficiency

LLM Application Stack

Backend & Cloud

DevOps Foundation

Cross-Functional Communication

Tools

Kubernetes

IaC

Kafka

Spark

Airflow

Job description

Title: Python + AI Lead

Location: Dallas, TX( Onsite )

Minimum Qualifications

• Overall Experience: 10+ years of total software engineering experience, including 5+ years of dedicated, hands-on Python development.
• Production AI Delivery: Proven track record of delivering at least one production‑grade AI/ML or LLM‑powered system through its complete lifecycle.
• AIDLC Proficiency: Practical understanding of the AI Development Life Cycle (data engineering, experimentation, evaluation, deployment, and monitoring).
• LLM Application Stack: Deep experience in prompt engineering, Retrieval-Augmented Generation (RAG), and integrating major LLM model provider APIs.
• Backend & Cloud: Strong foundation in designing/consuming RESTful APIs, containerization with Docker, and deploying backend systems on AWS, GCP, or Azure.
• DevOps Foundation: Solid grounding in Git version control and modern CI/CD release workflows.
• Cross-Functional Communication: Clear technical communication skills with a track record of collaborating across engineering, data science, and product teams.

Preferred Qualifications

• Agentic Frameworks: Experience with LangChain, LangGraph, LlamaIndex, or multi-agent orchestration frameworks.
• Vector Databases: Hands‑on work with Pinecone, Weaviate, pgvector, FAISS, and embedding retrieval strategies.
• MLOps / LLMOps: Exposure to MLflow, Weights & Biases, model registries, feature stores, and safety guardrails.
• Infrastructure & Data: Familiarity with Kubernetes, Infrastructure-as-Code (IaC), and streaming pipelines (Kafka, Spark, Airflow).

Core Tech Stack

• Languages & Frameworks: Python, FastAPI, Flask
• AI/LLM Tools: RAG, Agentic Frameworks, Vector DBs, MLOps/LLMOps Tooling
• DevOps & Cloud: Docker, CI/CD, AWS / GCP / Azure