Generative AI/LLM Engineer

Job description

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.

Key Responsibilities

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.

Qualifications

Qualifications

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 LangChain or LlamaIndex. Strong knowledge of RAG architectures, vector databases (Pinecone, Weaviate, Chroma, Milvus, Supabase), and semantic search. Experience with TTS/STT systems (OpenAI Whisper, Coqui TTS, ElevenLabs).

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.

Preferred

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 Success in This Role Looks Like 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