Generative AI​/LLM Engineer

Since opening our first self-storage facility in 1972,
Public Storage has grown to become the largest owner and operator of self-storage facilities in the world. With thousands of locations across the U.S. and Europe, and more than 170 million net rentable square feet of real estate, we're also one of the largest landlords.

We've been recognized as A Great Place to Work by the Great Place to Work Institute. And, our employees have also voted us as having Best Career Growth
, ranked us in the Top 5% for Work Culture
, and in the Top 10% for Diversity and Inclusion
.

We're a member of the S&P 500 and FT Global 500
. Our common and preferred stocks trade on the New York Stock Exchange.

Public Storage is the nation's leading self-storage provider, recognized for its iconic orange doors and commitment to delivering simple, reliable solutions to millions of customers across the country. We are expanding our creative team to enhance our consistent and engaging visual brand presence.

We are seeking a Generative AI / LLM Engineer with strong full-stack and Python development expertise to design, build, and deploy intelligent agents, Retrieval-Augmented Generation (RAG) systems, voice and image AI models, and automation workflows. This role is onsite in Frisco, TX and will work closely with product, engineering, and operations teams to deliver scalable, production-grade AI/Agent solutions that transform how Public Storage operates and engages with customers.

• LLM Agent Development
  :
  Design, train, and deploy conversational and task-specific AI agents leveraging cutting‑edge LLM architectures and tool integrations.
• RAG Pipelines
  :
  Build and optimize Retrieval-Augmented Generation systems for contextual, knowledge‑rich AI responses.
• Voice & Speech AI
  :
  Implement and integrate TTS (Text‑to‑Speech), STT (Speech‑to‑Text), and Whisper‑based transcription pipelines.
• Generative Image AI
  :
  Develop and integrate image generation, recognition, and analysis models for operational and customer‑facing use cases.
• Automation & Orchestration
  :
  Create workflow automations using tools like n8n, Make (Integromat), Zapier, and custom Python frameworks.
• Full‑Stack AI Delivery
  :
  Build APIs, microservices, and interfaces to deliver AI solutions end‑to‑end, from data ingestion to UI.
• Performance Optimization
  :
  Monitor, evaluate, and improve AI model performance for accuracy, latency, and scalability.
• Collaboration
  :
  Partner with cross‑functional teams to integrate AI capabilities into business processes and customer products.
• Security & Compliance
  :
  Ensure AI solutions adhere to corporate security policies, privacy regulations, and ethical AI principles.

• Bachelor’s or Master’s in Computer Science, AI/ML, Data Science, or related discipline.
• 5+ years of professional Python development experience (APIs, microservices, automation).
• Proven experience with LLMs (OpenAI, Anthropic, Meta, Mistral, etc.) and frameworks like Lang Chain or Llama Index.
• Strong knowledge of RAG architectures, vector databases (Pinecone, Weaviate, Chroma, Milvus, Supabase), and semantic search.
• Experience with TTS/STT systems (OpenAI Whisper, Coqui TTS, Eleven Labs).
• Hands‑on with generative image models (GPT‑Image‑1, Stable Diffusion, ComfyUI).
• Proficiency with automation/orchestration platforms (n8n, Make, Zapier).
• Cloud deployment experience (GCP, AWS, or Azure) for AI services.
• Solid understanding of AI prompt engineering best practices.

• Experience with containerization/orchestration (Docker, Kubernetes).
• MLOps experience with continuous training and deployment workflows.
• Frontend development skills (React, Next.js, or similar).
• Prior experience in self-storage, real estate, or retail technology environments.

• Deploying AI‑powered agents that improve customer self‑service and automate internal processes.
• Implementing RAG systems that provide contextually accurate responses across multiple business areas.
• Reducing manual workloads through advanced AI‑powered automation.
• Establishing reusable, scalable AI components for enterprise‑wide adoption.

• One of our values pillars is…