Future Works

AI Engineer

• As the Lead AI/Agent Architect, you own the technical track.
• You will design the agent orchestration model, the tool-use architecture, and the human-in-the-loop protocol, and you will stand up the secure sandbox environment the system runs against.
• You will turn a fragmented, document-heavy operational workflow into a secure, auditable, and extensible agent system, and you will validate exactly where automation ends and expert judgment begins.
• You are accountable for an architecture that processes a live transaction scenario end to end with human intervention only at documented gates, and that extends to adjacent workflows without a rebuild.
• Own the orchestrator agent that holds the deal state machine and routes work to one specialist agent per stage, defining stage handoff protocols and cross-stage integration.
• Design the typed tool layer as the integration seam that binds to sample data in the sandbox and to live systems in production, so the move to production is a connector change rather than a rebuild.
• Define the mandatory approval gates and review checkpoints, ensuring the agent never executes binding legal or financial actions without broker confirmation.
• Own the sandbox data model and test scenarios, and define the security, compliance, and data-governance approach.

Lead AI/Agent Architect

• Per-Stage Agent Build: Implement agent capabilities for individual workflow stages (for example engagement agreement generation, needs-assessment brief, market survey and long-list scoring, tour management, RFP and proposal analytics, lease abstraction, and close-out and invoicing), building to the orchestration model and stage handoff protocols defined by the Lead Architect.
• Tool & Integration Development: Build the typed tools the agents call: template population, market-data query, financial analytics (NER, TI, free rent, NPV), clause and lease-clause extraction, and document assembly.
• Data Pipelines: Build and maintain pipelines against sandbox and representative sample data, including the property availability data source.
• Human-in-the-Loop Implementation: Encode the approval gates and review checkpoints specified by the architect, so binding steps always route through a broker confirmation.
• Quality & End-to-End Testing: Validate components against deal-scenario data and participate in end-to-end testing across all eight stages, checking artifact quality and stage handoff integrity.
• Build-Phase Readiness: Participate in Phase 1 architecture workshops to ensure the build starts on solid foundations.

Lead AI/Agent Architect

AI/ML Engineer