Engagement Manager

As Engagement Manager, you will own 2-3 client relationships and lead engagements from initial discovery through implementation and ongoing expansion. You will sit at the intersection of consulting, AI solution design, and client success – translating ambiguous real estate problems into clear, executable plans and measurable outcomes.

• Own client relationships end-to-end, serving as the primary relationship manager and day-to-day point of contact.
• Lead discovery engagements (typically 2–3 weeks):
• Conduct stakeholder interviews across business, operations, and technology teams
• Map current-state processes and decision flows
• Identify, size, and prioritize pain points that are well-suited for AI intervention
• Translate business needs into structured problem statements, technical briefs, and solution hypotheses in partnership with Product and Engineering.
• Manage engagement scope, timelines, deliverables, and client communications with high precision and polish.
• Present findings, recommendations, and progress updates to senior audiences (VP , C-suite) with confidence.
• Drive implementation success by coordinating across internal technical teams and client stakeholders to support deployment and adoption.
• Identify expansion opportunities over time by linking delivered outcomes to additional high-value use cases.
• Serve as an internal feedback loop—bringing field insights back to improve the platform, packaging, and go-to-market motion.
• Travel to client sites as needed for relationship‑building and on‑site discovery sessions.
  
  What we’re looking for

• 7-10+ years of experience in tech enabled services consulting, strategy, or a high‑velocity, client‑facing role specifically in the commercial real estate domain
• Demonstrated ability to elicit business requirements from non‑technical stakeholders and translate them into clear, testable problem statements.
• AI‑native mindset: you actively use AI tools in your work and understand practical
• capabilities, limitations, and adoption considerations.
• Outstanding written and verbal communication: comfortable running executive meetings and producing crisp one‑pagers and client‑ready deliverables.
• Strong organizational skills and comfort managing multiple engagements simultaneously.
• Entrepreneurial orientation: energized by building new processes, templates, and playbooks in a lean environment.

• Experience at a Series A–C startup or in roles requiring significant cross‑functional ownership.
• Familiarity with AI/ML solution configuration and/or data pipeline concepts (you don’t need to build them, but should be able to speak to them).
• Track record of growing client relationships beyond the initial scope through demonstrated outcomes.

• Stakeholder interviews
• Process mapping and current‑state assessment
• Pain point prioritization and use‑case selection
• Output: prioritized roadmap + technical briefs + success metrics

• Partner with technical team on backend data work and AI solution configuration
• Validate hypotheses with client stakeholders through iterative check‑ins
• Output: configured solution(s), implementation plan, and readiness checklist

• Live deployment and adoption support
• Measurement and iteration against success metrics
• Relationship deepening and identification of next use cases
• Output: sustained outcomes and account growth plan