The role
Future Works is searching for a results-driven, AI-Enabled Product Manager to lead delivery of custom data and AI platforms for institutional real estate owners, operators and fund managers. These are fixed-fee, fixed-date engagements of roughly sixteen weeks, with payment tied to signed gates, and you are the day-to-day lead.
A typical cycle connects every system the client runs on (property accounting, third-party operator packages, investor and fund platforms, deal and leasing platforms, loan and JV documents, models in Excel and SharePoint) into one trusted asset record they own, hosted in their cloud environment, read-only and never writing back to source. On top of it, AI agents map new operator data, run data checks, abstract loan and JV terms, answer portfolio questions with sources cited and draft quarterly commentary, feeding the views each group needs: portfolio and asset performance, lease and tenant exposure, debt and covenants, equity and JV structure, business plan against locked underwriting, quarterly reporting and an exceptions log. Often the cycle also has to retire an incumbent platform by a contract date.
You own the plan, the gates and the scope line, supported by a data and technology lead, a full-stack engineer, a solution architect and a partner on business outcomes.
Key Responsibilities
Own the cycle end to end. Lead the full product development lifecycle across discovery workshops, data mapping, platform build, views, training and handover, against a fixed fee and a firm finish date.
Run gate-based delivery and hold the scope line. Define gate criteria, evidence and acceptance with the client before signature. Translate an ambitious scope into what one cycle can deliver, document what moves to later cycles, and manage change so a fixed fee stays fixed. Set a value baseline with client finance at the start and measure against it.
Put the data foundation first. Treat numbers that tie as the adoption bar. Work with the data lead on source mapping, data quality rules, exception routing to the responsible deal team, lineage and locked snapshots, before any view is built.
Define the views with the people who use them. Run workshops with asset management, finance, investor relations, deal teams and technology, and turn what they say into view specs, KPI definitions and acceptance criteria the client signs.
Decide where AI belongs, and where it does not. Work with engineering and data science on agent-based mapping, document extraction, retrieval with cited sources and drafted commentary, while keeping reported financial figures on fixed, auditable calculations the client approves.
Own the client relationship at working level. Be the primary contact for the executive sponsor, the business owner and the technology lead. Report progress plainly and surface problems before they land.
Land the retirement and the handover. Plan the history migration, the parallel run and the sign-off that the old system can be switched off, train teams by role inside the cycle, and transfer documentation and operating knowledge to the client's platform owner so their team builds what comes next.
Requirements
Must have
Experience. Minimum 5 years in product management with hands-on ownership of every phase of the PDLC, delivering custom software for external clients.
Real estate domain depth. At least 2 years inside or directly serving institutional real estate: an owner-operator, REIT, private equity real estate or fund manager, or a real estate technology or data vendor. You read a rent roll, an operating statement, a budget vs actual, a T-12, a loan abstract and a JV waterfall summary without a translator, and you know what WALT, DSCR, NOI and equity funded vs committed mean in practice.
Real estate systems fluency. Hands-on exposure to a property accounting system (Yardi, MRI or RealPage) plus at least one of Juniper Square, Altrio, VTS, ARGUS or a portfolio and asset management platform such as Pereview.
Data platform product experience. You have shipped a data warehouse, data lake, reporting or BI product where the adoption bar was trust in the numbers, not feature count, and can make product calls on ingestion, mapping, reconciliation, data quality rules, exception handling, lineage and immutable snapshots.
Technical knowledge in AI and software development. Strong grasp of LLM-based extraction, retrieval with cited sources, agent workflows and human-in-the-loop approval, with the ability to turn business requirements into specifications design and engineering can build from.
Microsoft data stack literacy. Comfortable delivering into a client's Microsoft environment (Azure, Fabric or Synapse, Power BI), including single sign-on, role and fund-level permissions, audit logging and test environments.
Fixed-fee consulting delivery. Track record on milestone or gate-based engagements where payment depends on acceptance, including writing acceptance criteria that survive a client signature.
Leadership and client presence. 5 to 7+ years leading multidisciplinary teams (design, engineering, data), and comfortable in the room with a CFO, COO, head of asset management or head of technology, delivering unwelcome news early and clearly.
Analytical and data-driven. Able to define KPIs, interrogate a number, find why actuals diverge from a plan and decide from evidence.
Practicalities. Proficiency in our project software suite (GSuite, ClickUp, Figma, Jira), and overlap with US Eastern business hours for workshops, gate reviews and training.
Strongly preferred
Experience retiring or replacing an incumbent platform against a contract date, including a parallel run.
Experience with quarterly investor reporting cycles, fund-level reporting or DDQ response processes.
Data governance experience: ownership models, stewardship, and approval of mappings and thresholds by the business rather than by IT.
Benefits & Perks
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.
