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Public Storage · 8 hours ago

Full Stack Technical Lead (AI Systems & Distributed Architecture)

Plano, TX

Full-time

Hybrid

Senior Level, Lead/Staff

8+ years exp

Public Storage is the largest owner and operator of self-storage facilities in the world, recognized for its commitment to delivering reliable solutions to millions of customers. They are seeking a visionary Full Stack Technical Lead to spearhead the development of AI-powered applications, bridging complex business requirements with high-performance engineering while leading a team of developers.

Property ManagementReal EstateReal Estate Investment

No H1B

U.S. Citizen Only

Responsibilities

Drive architectural decisions and provide thought leadership on AI innovation and system enhancements

Lead, mentor, and grow a team of 5–10 engineers

Translate complex business requirements into technical roadmaps and provide high-accuracy effort estimations

Lead comprehensive code reviews and implement proactive refactoring strategies to manage technical debt

Partner closely with Product, Design, and DevOps teams to ensure seamless deliveries

Act as the technical liaison for stakeholders, maintaining clear documentation and resolving team conflicts

Qualification

.NETASP.NET CoreCQRSMicroservicesSQL ServerTypeScriptReactAngularVue.jsCloud ProvidersKubernetesCI/CDAI AgentsPythonEthics in AITeam LeadershipDocumentation

Required

8–10+ years of professional full-stack development experience, with a proven track record of delivering AI-driven solutions

Mastery of .NET (8)/Core and ASP.NET Core for high-scale applications

Deep expertise in CQRS, Event Sourcing, and Domain-Driven Design (DDD)

Proven experience building microservices and managing complex API ecosystems

Expert-level SQL Server proficiency (complex schema design, performance tuning, and optimization)

Advanced proficiency in TypeScript and modern frameworks (React, Angular, or Vue.js)

Practical experience implementing micro-frontend architectures to support modularity

Hands-on experience with cloud providers (Azure, AWS, or GCP) and container orchestration via Kubernetes

Mastery of caching strategies (e.g., Redis) and a 'security-first' approach to development and compliance

Experience with CI/CD pipeline design and automation

Experience with enterprise monitoring and logging tools (e.g., Application Insights, Datadog, ELK)

Preferred

Experience building autonomous AI agents and multi-agent systems

Integrate API with configured AI providers (e.g., Azure AI/OpenAI) to perform tasks such as chat completion, summarization, classification, and extraction

Advanced integration of Large Language Models, including prompt engineering, function calling, and embedding management

Proficiency with vector databases (e.g., Pinecone, Milvus) for RAG-based applications

Knowledge of model selection, evaluation frameworks, cost optimization, and fine-tuning strategies

Familiarity with Python for prototyping models, utilizing ML libraries, or integrating with Python-based AI services

A deep understanding of ethics in AI, including bias mitigation and data privacy standards