Senior AI Product Manager

Future Works

About The Position

Future Works is seeking 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. Engagements are fixed-fee, fixed-date projects lasting roughly sixteen weeks, with payments tied to signed gates. The Product Manager is the day-to-day lead and owns the plan, gates, and scope, supported by a data and technology lead, full-stack engineer, solution architect, and partner focused on business outcomes. A typical engagement connects client systems—including property accounting, operator packages, investor and fund platforms, deal and leasing platforms, loan and JV documents, and spreadsheets and SharePoint—into a trusted asset record hosted in the client’s cloud environment. The system is read-only and does not write back to source systems. AI agents may map incoming operator data, check data quality, abstract loan and JV terms, answer portfolio questions with cited sources, and draft quarterly commentary. The platform provides views for portfolio and asset performance, lease and tenant exposure, debt and covenants, equity and JV structure, business plans against locked underwriting, quarterly reporting, and exceptions. Engagements may also include retiring an incumbent platform by a specified contract date. The Product Manager leads delivery from discovery through data mapping, platform build, views, training, and handover. They define and manage acceptance gates and scope, establish and measure a value baseline, prioritize trusted and auditable data, define views with client users, determine appropriate uses of AI, maintain the working-level client relationship, and oversee platform retirement and knowledge transfer.

Requirements

At least 5 years of product management experience, with hands-on ownership of every phase of the product development lifecycle and delivery of custom software for external clients.
At least 2 years working inside or directly serving institutional real estate, such as an owner-operator, REIT, private equity real estate firm, fund manager, or real estate technology or data vendor.
Ability to interpret rent rolls, operating statements, budget-versus-actual reports, T-12s, loan abstracts, and JV waterfall summaries, and practical understanding of WALT, DSCR, NOI, and equity funded versus committed.
Hands-on exposure to a property accounting system such as Yardi, MRI, or RealPage, plus at least one of Juniper Square, Altrio, VTS, ARGUS, or a portfolio and asset management platform such as Pereview.
Experience shipping a data warehouse, data lake, reporting, or BI product where adoption depended on trust in the numbers; ability to make product decisions concerning ingestion, mapping, reconciliation, data quality rules, exception handling, lineage, and immutable snapshots.
Strong understanding of LLM-based extraction, retrieval with cited sources, agent workflows, and human-in-the-loop approval; ability to turn business requirements into specifications for design and engineering.
Comfort delivering in a client Microsoft environment, including Azure, Fabric or Synapse, and Power BI, with knowledge of single sign-on, role- and fund-level permissions, audit logging, and test environments.
Track record delivering fixed-fee, milestone- or gate-based consulting engagements where payment depends on acceptance, including writing acceptance criteria that withstand client signature.
5 to 7+ years leading multidisciplinary design, engineering, and data teams; comfort working with senior client stakeholders such as CFOs, COOs, heads of asset management, and heads of technology, and communicating unwelcome news early and clearly.
Ability to define KPIs, investigate data, identify why actuals diverge from plans, and make evidence-based decisions.
Proficiency with GSuite, ClickUp, Figma, and Jira.
Availability overlapping with US Eastern business hours for workshops, gate reviews, and training.

Nice To Haves

Experience retiring or replacing an incumbent platform by a contract date, including running systems in parallel.
Experience with quarterly investor reporting cycles, fund-level reporting, or DDQ response processes.
Data governance experience, including ownership models, stewardship, and business approval of mappings and thresholds.

Responsibilities

Own the full product development lifecycle across discovery workshops, data mapping, platform build, views, training, and handover, within a fixed fee and firm finish date.
Define gate criteria, evidence, and acceptance with the client before signature; translate scope into deliverables for the cycle; document work deferred to later cycles; and manage changes to preserve the fixed fee.
Set a value baseline with client finance at the start of the engagement and measure results against it.
Work with the data lead on source mapping, data quality rules, exception routing, lineage, and locked snapshots before views are built.
Run workshops with asset management, finance, investor relations, deal teams, and technology; translate needs into view specifications, KPI definitions, and client-approved acceptance criteria.
Work with engineering and data science to determine appropriate uses of agent-based mapping, document extraction, cited-source retrieval, and drafted commentary, while keeping reported financial figures on fixed, auditable calculations approved by the client.
Serve as the primary working-level contact for the executive sponsor, business owner, and technology lead; communicate progress clearly and surface problems early.
Plan history migration, parallel runs, and sign-off for switching off the incumbent system.
Train client teams by role during the cycle and transfer documentation and operating knowledge to the client’s platform owner.