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.
What you’ll do
- 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
Required
- 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.
Preferred
- 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.
How engagements work (3-phase model)
1. Discovery (Weeks 1–3)
- Stakeholder interviews
- Process mapping and current-state assessment
- Pain point prioritization and use-case selection
- Output: prioritized roadmap + technical briefs + success metrics
2. Build (Weeks 4–8)
- 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
3. Implementation & Expansion (Ongoing)
- 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