Job Details

Context

At Landmark, we believe better living starts with exceptional experiences for owners, residents, and our operating teams. Born out of the engineering labs at co-living leader Bungalow, Landmark is reimagining property management from the ground up. Landmark is building a future where AI and human expertise work together to deliver responsive service, smart operations, and vibrant communities that people are proud to call home. As we scale, we're seeking a forward-thinking AI Applications Engineer to help bring this vision to life.

The AI Applications Engineer is at the core of our mission: building intelligent solutions that automate and enhance property management workflows. You'll design and implement AI-driven features, ensuring our solutions are scalable, reliable, and impactful on day-to-day operations. We'll work together to build and you might own:

• semantic search spanning multiple systems


• automatic support request triaging and classification for owners and residents


• interactive communications with owners and residents


• translating natural-language inquiries into concrete data visualizations


• image content classification


• multi-agent systems supporting end-to-end maintenance workflow automations


• and more…

If you're passionate about pushing the AI frontier to solve real-world challenges and fundamentally shape automation in one of the world's most essential industries, then let's connect!

Your Mission

AI Feature Development: Design and develop AI-driven applications and features that automate and augment property management processes across multiple systems [e.g. automating customer inquiry handling, maintenance request coordination, labor dispatching, leasing and marketing optimizations, and internal reporting].

Semantic Search: Develop semantic search capabilities [e.g. RAG - leveraging embeddings and vector databases] to enable intelligent querying of both structured and unstructured data, so users can quickly find relevant information across our platform.

Agentic AI Solutions: Build agent-based AI workflows [using frameworks like LangGraph] that can interact with tools and databases to perform multi-step tasks autonomously, with appropriate human-in-the-loop oversight for critical decisions.

Tuning + Optimization: Fine-tune and customize AI/ML models [using techniques such as LoRA] to improve performance on domain-specific problems and continuously evaluate their effectiveness.

Integration + Deployment: Own your software end-to-end from initial development to deployment. Containerize and deploy AI services using Docker and cloud infrastructure. Ensure these systems are configurable, scalable, secure, reliable, observable, and maintainable.

Cross-Functional Collaboration: Work closely with Operations and Data teams to identify opportunities for new automations and optimizations. Translate real-world property management challenges into effective AI-powered solutions, and iterate based on feedback.

Frontier Exploration: Stay up-to-date with the latest advancements in AI [LLMs, tools, frameworks] and proactively bring new ideas and experimental prototypes to the team. We encourage following your curiosity to keep Landmark at the cutting edge of AI-powered automations.

Minimum Viable Skillset

• Experience: 2+ years with a strong focus on Python and AI applications


• Tools: LangChain, LangGraph, HuggingFace, MCP, or similar


• Core Skills: Strong software engineering skills. Proficiency with Linux environments and software integration/deployment, including containerization, RESTful API usage, dependency management, and working with databases [SQL or NoSQL].


• Hands On, All In: Thrives in lean, high-impact startup teams. Owns and creates systems end-to-end with minimal oversight.

Perks + Parameters

• Salary: $160K – $190K [depending on experience]


• Equity: Competitive


• Location: Presidio, San Francisco, CA [hybrid - 3 days/week]


• Benefits: Health, dental, and vision

The Stack

• AI: LangChain, Pinecone, PyTorch, Gradio


• Backend: Python, Django, GraphQL, REST APIs, FastAPI


• Data: PostgreSQL, Redshift, Metabase


• Infrastructure: AWS, Airflow, Vercel


• Observability: Sentry, AWS Cloudwatch, Slack


• Frontend: Vue, Vuetify, TypeScript