Python + AI Lead

Cloudious • Dallas, TX

1d • Hybrid

About The Position

The Python + AI Lead will use strong, current Python expertise and software development experience to deliver AI/ML or LLM-powered systems to production and support them throughout their life cycle. The role involves practical work across the AI Development Life Cycle, including data handling, experimentation, evaluation, deployment, and monitoring.

The position also involves developing LLM applications using prompt engineering, retrieval-augmented generation (RAG), and APIs from major model providers; designing and consuming RESTful APIs; and building scalable backend services. The Lead will work across engineering, data, and product teams. The role is based in Dallas, Texas, in a hybrid work arrangement, with a stated duration of 12+ months.

Requirements

• 10+ years of overall experience.
• 5+ years of professional software development experience, with strong, current Python expertise.
• Demonstrable experience delivering at least one AI/ML or LLM-powered system to production and supporting it through its life cycle.
• Practical familiarity with the AI Development Life Cycle, including data handling, experimentation, evaluation, deployment, and monitoring.
• Hands-on experience with LLM application development, including prompt engineering, RAG, and integrating APIs from major model providers.
• Proficiency in designing and consuming RESTful APIs and building scalable backend services.
• Working knowledge of AWS, GCP, or Azure and containerization with Docker.
• Solid grounding in Git and CI/CD workflows.
• Strong communication skills and ability to work across engineering, data, and product teams.

Nice To Haves

• Experience with agentic frameworks and orchestration, such as LangChain, LangGraph, LlamaIndex, or multi-agent frameworks.
• Familiarity with vector databases such as Pinecone, Weaviate, pgvector, and FAISS, and embedding-based retrieval.
• Exposure to MLOps/LLMOps tooling, including MLflow, Weights & Biases, model registries, and feature stores.
• Experience with Kubernetes and infrastructure-as-code.
• Understanding of model evaluation, responsible AI, safety guardrails, and observability for LLM systems.
• Background with data pipelines and streaming, such as Kafka, Spark, or Airflow.

Responsibilities

• Deliver AI/ML or LLM-powered systems to production and support them through their life cycle.
• Work across the AI Development Life Cycle, including data handling, experimentation, evaluation, deployment, and monitoring.
• Develop LLM applications using prompt engineering, RAG, and APIs from major model providers.
• Design and consume RESTful APIs and build scalable backend services.
• Collaborate across engineering, data, and product teams.

What This Job Offers

• Career Level: Senior
• Education Level: No Education Listed