Senior Technical Lead, AI & Automation

Company Description

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 Senior Technical Lead, AI to serve as the technical authority for AI architecture, system design, and delivery across the AI POD. This role is responsible for shaping how AI solutions are designed, built, deployed, and maintained across LLM agents, RAG systems, to automation workflows and production infrastructure.

This is a hands‑on technical leadership role, not a people manager. You will guide engineers, influence design decisions, establish standards, and ensure AI solutions are scalable, secure, and production‑ready while remaining deeply involved in implementation.

• Act as the technical lead for the AI POD, mentoring engineers and helping unblock complex technical challenges.
• Establish engineering standards for AI workflows, agent behavior, evaluation, observability, and lifecycle management.
• Ensure consistency across AI solutions while allowing flexibility for rapid experimentation.
• Lead the design and implementation of LLM‑powered agents, tool‑calling frameworks, and multi‑step reasoning workflows.
• Architect and optimize Retrieval‑Augmented Generation (RAG) pipelines using vector databases and enterprise knowledge sources.
• Ensure workflows are resilient, observable, cost‑efficient, and maintainable at scale.
• Partner with cloud and infrastructure teams to design scalable AI platforms across GCP, AWS, or Azure.
• Ensure AI systems comply with corporate security standards, data privacy requirements, and ethical AI principles.

• Bachelor’s or Master’s in Computer Science, AI/ML, Data Science, or related discipline.
• 7+ 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 AI‑driven automation and orchestration platforms (n8n, Make, Zapier).
• Cloud‑native experience deploying and operating AI workloads in GCP, AWS, or Azure.
• Strong system design skills with the ability to balance speed, quality, and long‑term maintainability. 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

• The AI POD ships reliable, scalable, production‑ready AI solutions at speed.
• Clear, reusable AI architectures and standards are adopted across teams.
• AI workflows are observable, secure, and cost‑efficient;
  Not brittle experiments.
• Engineers are unblocked, supported, and guided by strong technical leadership.

• One of our values pillars is to work as One Team and we believe that there is no replacement for in‑person collaboration but understand the value of some flexibility. Public Storage teammates are expected to work in the office five days…