Senior AI Product Manager

Jobgether; Oregon; Hybrid; USD 180,000 - 240,000; Full time

Benefits offered by this job

Fully remote working environment

Equity opportunity

Performance-based bonus

Flexible schedule

Professional development

Job summary

Jobgether is seeking a Senior AI Product Manager to lead the development of AI-powered data platforms for institutional real estate clients from the United States. This remote-first role emphasizes autonomous delivery, end-to-end product ownership, and transforming complex datasets into reliable AI-enabled solutions.

You will manage fixed-fee, milestone-based engagements, align cross-functional teams across engineering, data, and operations, and ensure transparent governance, auditable AI

Qualifications

• Minimum 5 years in product management leading full lifecycle for external clients.
• 2+ years in institutional real estate sector or related services.
• Strong understanding of real estate operations, rent rolls, NOI and related metrics.
• Experience delivering data platforms, data warehouses/lakes, BI dashboards.
• Proficiency with AI-enabled workflows, information extraction, and auditable outputs.
• Ability to translate business needs into technical specs for engineering teams.
• Excellent written and verbal communication with executive sponsors.

Responsibilities

• Lead end-to-end product development lifecycle from discovery to handover.
• Define milestones, gates, acceptance criteria, and measurable outcomes with clients.
• Establish data foundations, mappings, quality rules, and governance.
• Facilitate workshops with asset management, finance, and technology stakeholders.
• Identify opportunities to integrate AI agents and automation into workflows.
• Manage client relationships, risks, and project expectations with clear recommendations.
• Coordinate data migration, testing, and platform retirement.
• Develop training and comprehensive documentation for handover.
• Measure value baselines and drive continuous improvement of processes and AI-enabled workflows.

Skills

Product management

AI/ML knowledge

Data platforms

Real estate domain

LLM-based solutions

Stakeholder management

Client facing

Cross-functional leadership

Job description

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior AI Product Manager based in the United States.

We are seeking an experienced Senior AI Product Manager to lead the development and delivery of innovative AI-powered data platforms for institutional real estate owners, operators, and investment managers. In this highly autonomous role, you will oversee end-to-end product delivery, transforming complex business requirements and fragmented data ecosystems into reliable, intelligent solutions. You will manage fixed-fee, milestone-based engagements, taking ownership of project scope, timelines, budgets, and client relationships. Working closely with multidisciplinary teams across engineering, data, architecture, and business functions, you will ensure that every solution delivers measurable operational value. You will also play a key role in integrating AI agents, advanced analytics, and automation into enterprise workflows while maintaining data accuracy, transparency, and accountability. This is an opportunity to shape the future of AI-enabled professional services in a high-performance, remote-first environment that values innovation, precision, and continuous improvement.

Accountabilities

End-to-End Product Management

Lead the complete product development lifecycle, from discovery workshops and requirements gathering to data mapping, platform development, user acceptance, training, and final handover. Ensure delivery against agreed budgets, milestones, and fixed deadlines.

Project Planning and Scope Management

Define project milestones, delivery gates, acceptance criteria, and measurable outcomes in collaboration with clients. Translate ambitious business objectives into realistic delivery plans, manage scope changes, prioritize requirements, and ensure contractual commitments are met.

Data Foundation and Governance

Establish reliable data foundations by coordinating source-system mapping, data quality rules, reconciliation processes, exception management, data lineage, and immutable snapshots. Work closely with technical teams to ensure data accuracy and consistency before developing reporting and analytical solutions.

Stakeholder Engagement and Product Discovery

Facilitate workshops with asset management, finance, investor relations, investment teams, and technology stakeholders. Translate business needs into detailed product specifications, KPI definitions, dashboards, reporting views, and acceptance criteria.

AI Strategy and Implementation

Identify opportunities to integrate AI agents and intelligent automation into business processes, including data mapping, document extraction, information retrieval, and automated reporting. Collaborate with engineering and data science teams to implement LLM-based solutions while ensuring financial reporting relies on auditable calculations and approved data.

Client Relationship Management

Serve as the primary day-to-day contact for executive sponsors, business owners, and technology leaders. Communicate project progress, manage expectations, address risks, and proactively escalate challenges with clear recommendations.

Platform Migration and Implementation

Coordinate historical data migration, parallel testing, platform validation, and retirement of legacy systems. Ensure successful implementation, user adoption, and knowledge transfer before project completion.

Training and Handover

Develop role-specific training programs and comprehensive documentation. Transfer operational knowledge to client platform owners, enabling internal teams to maintain, operate, and further develop the implemented solutions.

Performance Measurement and Continuous Improvement

Establish measurable value baselines with client finance teams and track business outcomes throughout delivery. Identify opportunities to improve product processes, data governance, operational efficiency, and AI-enabled workflows.

Requirements

• At least 5 years of product management experience, with hands-on ownership of the full product development lifecycle and a proven track record delivering custom software solutions for external clients.
• Minimum 2 years of experience within or directly serving the institutional real estate sector, including owner-operators, REITs, private equity real estate firms, fund managers, or real-estate technology and data providers.
• Strong understanding of institutional real estate operations and financial concepts, including rent rolls, operating statements, budget-versus-actual reporting, T-12 statements, loan abstracts, joint venture waterfall summaries, WALT, DSCR, NOI, and committed versus funded equity.
• Practical experience with property accounting platforms such as Yardi, MRI, or RealPage, alongside at least one real estate investment or portfolio management solution such as Juniper Square, Altrio, VTS, ARGUS, or Pereview.
• Proven experience delivering data platform products, including data warehouses, data lakes, reporting solutions, or business intelligence platforms, with a strong focus on data reliability, reconciliation, governance, and user trust.
• Strong technical understanding of AI and software development, particularly LLM-based information extraction, retrieval-augmented generation with cited sources, agent-based workflows, and human-in-the-loop approval processes.
• Ability to translate business requirements into clear product specifications, technical requirements, and implementation plans for engineering and design teams.
• Familiarity with the Microsoft data ecosystem, including Azure, Microsoft Fabric, Synapse, and Power BI, as well as enterprise requirements such as single sign-on, role-based and fund-level permissions, audit logging, and testing environments.
• Demonstrated experience managing fixed-fee consulting engagements and milestone-based delivery models, including defining measurable acceptance criteria and managing contractual commitments.
• At least 5–7 years of experience leading multidisciplinary teams across product, design, engineering, and data functions.
• Strong executive presence and client-facing communication skills, with the ability to engage confidently with CFOs, COOs, heads of asset management, and technology leaders.
• Excellent analytical and problem-solving capabilities, including KPI development, financial analysis, performance tracking, and identifying discrepancies between actual results and business plans.
• Proficiency with project collaboration and productivity tools such as Google Workspace, ClickUp, Figma, and Jira.
• Availability to work with significant overlap with US Eastern business hours for client workshops, milestone reviews, and training sessions.
• Strongly preferred qualifications: Experience replacing or retiring legacy software platforms within strict contractual deadlines, including managing parallel runs and migration processes.
• Familiarity with quarterly investor reporting, fund-level reporting, and due diligence questionnaire (DDQ) processes.
• Experience implementing data governance frameworks, including business ownership, data stewardship, and stakeholder approval of data mappings, quality thresholds, and reporting standards.

Benefits

• Competitive compensation package with opportunities to participate in company equity.
• Performance-based bonus opportunities.
• Substantial participation in company profits, providing additional opportunities to share in business success.
• Clear career progression opportunities, including a potential pathway to C-level leadership based on performance.
• Fully remote working environment with flexibility and autonomy.
• All-expenses-paid company retreats in unique locations, offering opportunities for team connection, collaboration, learning, and professional development.
• Opportunity to work in an AI-native organization at the forefront of operational AI and data transformation.
• High-performance culture built around autonomy, innovation, transparency, collaboration, and continuous learning.
• Opportunity to lead impactful projects and deliver advanced AI-powered solutions for major organizations in high-impact industries.