About UnlockLand
UnlockLand is building the world’s first AI Operating System for Real Estate Development. Our platform combines zoning intelligence, generative planning, ROI-based financial modeling, and geospatial workflows into a real-time decision-making environment.
We are active in Canada, the United States, Australia, and Saudi Arabia, and are supported by top-tier accelerators and international venture capital. Our mission is to compress months of consulting and regulatory complexity into minutes of automated intelligence.
Role Overview
As a Senior Backend Engineer focused on AI infrastructure and multi-agent workflows, you will work at the core of UnlockLand’s intelligent systems. You will architect and implement AI pipelines that power zoning interpretation, generative design prompts, financial evaluations, and dynamic plan recommendation engines.
This role sits at the intersection of backend engineering, AI workflows, and prompt engineering – with direct impact on real estate development workflows globally.
Responsibilities
- Design and build modular, scalable backend services using Python, Django, and FastAPI
- Implement prompt management systems (e.g. via LangChain, CrewAI, PromptLayer, or internal frameworks)
- Structure and maintain multi-agent workflows for zoning analysis, financial modeling, and design automation
- Integrate with third-party LLMs (OpenAI, Gemini, Claude) and/or fine-tuned local models (Vertex AI)
- Optimize AI call chains for latency, caching, token usage, and structured output reliability
- Develop and maintain APIs consumed by our frontend, mobile, and internal tooling layers
- Collaborate with frontend, GIS, and data teams to define schema, event flows, and modular services
- Set up job queues, API rate control, audit logging, and distributed job orchestration
- Work within a CI/CD environment powered by Docker, GitHub Actions, and Google Cloud Run
Qualifications
Required:
- 4+ years of experience in backend development (Python preferred)
- Strong experience building REST APIs using Django / DRF or FastAPI
- Experience designing modular services or microservice architectures
- Familiarity with at least one LLM orchestration framework (LangChain, CrewAI, semantic kernel, etc.)
- Understanding of prompt engineering principles, tokenization, RAG, and structured chaining
- Hands-on experience deploying AI agents or multi-stage workflows into production
- Comfortable working in Docker-based CI/CD environments (GitHub Actions + GCP)
- Experience working with PostgreSQL, Redis, and cloud storage systems (GCS/S3)
Preferred:
- Experience with AI planning, constraint solving, or graph-based task execution
- Prior experience working on PropTech, UrbanTech, or geospatial data platforms
- Exposure to GCP components such as Cloud Run, Pub/Sub, Cloud Functions, Vertex AI
- Familiarity with vector databases (e.g., Pinecone, Weaviate, Qdrant, Chroma)
- Interest in translating government regulation (e.g., zoning bylaws) into AI-readable logic
What We Offer
- A key role in designing intelligent systems that reshape how cities grow
- High-impact, high-ownership position within a fast-moving AI product team
- Opportunities to lead foundational backend decisions with long-term impact
- Full relocation and visa support for international candidates
- Equity options and performance-based bonuses
- Career growth toward technical leadership or AI infrastructure lead roles
