Position Summary
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.
Core Responsibilities
- 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.
Qualifications :
- Bachelors or Masters 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 LangChain or LlamaIndex.
- 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.
Preferred:
- Experience with containerization/orchestration (Docker Kubernetes).
- MLOps experience with continuous training and deployment workflows.
- Frontend development skills (React or similar).
- Prior experience in self-storage real estate or retail technology environments
Success in This Role Looks Like
- 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.
Additional Information :
Workplace
- One of our values pillars is to work as OneTeam 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 each week with the option to take up to three flexible remote days per month.
Public Storage is an equal opportunity employer and embraces diversity. We do not discriminate on the basis of race color religion sex sexual orientation gender identity national origin age disability or any other protected status. All qualified candidates are encouraged to apply.
**Sponsorship for Work Authorization is not available for this posting. Candidates must be authorized to work in the U.S. without requiring sponsorship now or in the future.**
Remote Work :
No
Employment Type :
Full-time
Position SummaryWe 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...
Position Summary
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.
Core Responsibilities
- 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.
Qualifications :
- Bachelors or Masters 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 LangChain or LlamaIndex.
- 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.
Preferred:
- Experience with containerization/orchestration (Docker Kubernetes).
- MLOps experience with continuous training and deployment workflows.
- Frontend development skills (React or similar).
- Prior experience in self-storage real estate or retail technology environments
Success in This Role Looks Like
- 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.
Additional Information :
Workplace
- One of our values pillars is to work as OneTeam 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 each week with the option to take up to three flexible remote days per month.
Public Storage is an equal opportunity employer and embraces diversity. We do not discriminate on the basis of race color religion sex sexual orientation gender identity national origin age disability or any other protected status. All qualified candidates are encouraged to apply.
**Sponsorship for Work Authorization is not available for this posting. Candidates must be authorized to work in the U.S. without requiring sponsorship now or in the future.**
Remote Work :
No
Employment Type :
Full-time
View more
View less