Lead AI/Agent Architect

Role Description

We are running an engagement to design and build an AI agent system that manages a complex, high-value transaction workflow for a large enterprise client, from initial engagement through close-out, across a multi-stage process.

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. Working closely with AI/ML Engineers, a Lead Business Analyst, and the Engagement Director, 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.

Key Responsibilities

• Agent Orchestration Design: 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.
• Tool-Use Architecture: Design the typed tool layer (template population, market-data query, financial analytics, clause extraction, document assembly) 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.
• Human-in-the-Loop Protocol: Define the mandatory approval gates (engagement agreement issuance, LOI execution, lease signature, invoice issuance) and review checkpoints (requirements-brief sign-off, short-list, negotiation positioning), ensuring the agent never executes binding legal or financial actions without broker confirmation.
• Secure Sandbox & Data Governance: Own the sandbox data model and test scenarios, and define the security, compliance, and data-governance approach: data residency, PII handling, audit logging, and a zero-retention policy with no training on client or deal data.
• Feasibility Validation: Validate the technical feasibility of the automation hypotheses stage by stage and translate the automation boundary findings into architecture.
• Extensibility by Design: Architect the system with explicit extensibility to Agency (Landlord Rep) workflow and other brokerage lines, producing a platform foundation rather than a point solution.
• Cross-Functional Technical Leadership: Lead and direct the AI/ML Engineers through the build phases, managing orchestration and cross-stage integration while engineers build per-stage capabilities in parallel.

Qualifications

• 8+ years in software engineering, AI/ML, or solutions architecture, with a strong track record of designing and shipping production-grade systems, and recent hands-on experience architecting LLM or multi-agent systems.
• Agent Systems Expertise: Deep, hands-on experience with agent orchestration, tool and function calling, state management, and retrieval, ideally in production rather than prototypes.
• Technical Breadth: Expert Python (or equivalent), API and connector design, typed tool and interface design, and modern data stores such as PostgreSQL.
• Systems Thinking: Proven ability to design end-to-end solutions connecting data pipelines, model services, business logic, and user-facing applications under real operational constraints.
• Human-in-the-Loop & Governance: Experience designing guardrails, approval gates, auditability, and traceability for high-stakes, document-heavy domains where decisions must be explainable and reviewable.
• Domain Knowledge: Previous experience in commercial real estate, legal, financial services, or another structured, document-driven transaction domain is highly preferred.
• Path to Production: Practical experience taking a sandbox or prototype system to production through connector and tool abstraction, including performance, monitoring, deployment, and rollback.
• AI-Native Workflow: Comfort utilizing LLM code assistants and agentic engineering to improve speed, quality, and architectural clarity.
• Agile Execution: Ability to work effectively in fast, hypothesis-driven delivery cycles where the focus is on proving value quickly without creating unnecessary technical debt.

Benefits

• Work from anywhere, forever - We are a fully remote and global team. We trust you to manage your time and energy to deliver exceptional results.
• Connect deeply - We gather for immersive, all-expenses-paid company retreats in unique locations to connect, learn, and grow together.
• Share in the upside - A competitive compensation package including equity, bonuses, substantial participation in company profits with a clear growth path to C-Level leadership based on performance.