Greystar is a leading global real estate platform, and they are seeking a Full Stack AI Engineer to design, build, and ship AI-powered products. This role involves working across the stack to create solutions that improve the management and optimization of real estate assets.
Responsibilities:
- Design and implement full stack features across our digital products including GPS (our asset management platform), Greystar.com, and internal AI tools
- Build and integrate AI/ML capabilities into production applications — including LLM-powered workflows, MCP tool integrations, retrieval-augmented generation (RAG), and predictive analytics
- Own features from concept through deployment: frontend UI, API design, backend services, data pipelines, and AI model integration
- Rapidly prototype and iterate on AI-driven features, moving from proof of concept to production with speed and quality
- Build responsive, accessible frontend interfaces using modern frameworks (React/Next.js or similar)
- Design and implement scalable backend services and APIs (Python, Node.js, or similar) that serve both human users and AI agents
- Work with cloud infrastructure (Azure preferred) including serverless functions, container orchestration, and managed AI/ML services
- Ensure production systems are reliable, observable, and secure — with appropriate monitoring, logging, and error handling
- Partner with Product Management, Design, Business owners, and Data Engineering to define and deliver high-impact features
- Participate in architectural decisions that affect the broader platform, advocating for simplicity, maintainability, and AI-readiness
- Collaborate with other engineers on AI integration patterns, prompt engineering, and modern development practices
Requirements:
- 5+ years of professional software engineering experience shipping production applications
- Strong proficiency in both frontend (React, TypeScript, modern CSS) and backend (Python, Node.js, or Go) development
- Deep experience with AI coding tools like Cursor, Codex, Claude Code, etc
- Experience designing and building RESTful APIs, microservices, and event-driven architectures
- Solid understanding of relational and non-relational databases, caching strategies, and data modeling
- Experience with CI/CD pipelines, infrastructure as code, and cloud platforms (Azure preferred, AWS/GCP acceptable)
- Hands-on experience integrating LLMs (OpenAI, Anthropic, or similar) into production applications — including prompt engineering, function calling, and agent workflows
- Familiarity with RAG architectures, vector databases, embedding models, and MCP (Model Context Protocol) or similar tool-use patterns
- Understanding of when to build vs. buy AI capabilities and how to evaluate AI vendor tools critically
- Personal projects or portfolio demonstrating AI-powered applications you've built — we want to see what you've shipped
- AI-first mindset — you naturally look for opportunities to automate, augment, and accelerate with AI in your daily work and product development
- Strong written and verbal communication skills; able to explain technical trade-offs to non-technical stakeholders
- Comfort with ambiguity and a bias toward shipping iteratively over waiting for perfection
- Collaborative approach; you work well across product, design, data, and business teams
- Proficient with modern development tools: Git, Linear (or similar), VS Code/Cursor
- Knowledge of cloud platforms (Azure preferred), containerization (Docker/Kubernetes), and modern DevOps practices
- Familiarity with design systems and component libraries; able to collaborate effectively with designers
- Experience in real estate, property management, or asset management is a strong plus
- Familiarity with marketplace or multi-sided platform products
- Experience working in data-intensive environments where data quality and governance matter