Key skills
AI product managementAI/ML feature shippingLarge language models (LLMs)Prompt engineeringContext engineeringRetrieval-augmented generation (RAG)Rapid prototyping tools ClaudeRapid prototyping tools CursorRapid prototyping tools ReplitCustomer interviewsProduct discoveryCommercial real estate (CRE)ProptechVertical SaaSDecision making under ambiguityStrategic thinkingAIMLLLMClaudeRAGAgenticSaaSPrototypingProduct ManagementCommunication
About this role
Buildout is the AI deal engine for CRE brokerages, automating every step from first contact to commission. The Senior Product Manager will own the strategy and roadmap for AI, enhancing broker workflows and ensuring high-quality AI skills are developed and deployed.
Responsibilities:
- Set the vision, strategy, and roadmap for AI: decide which skills we build, in what order, and why
- Be customer facing: spend real time with customers, watch how they actually work, test AI skills against their live workflows, and carry what you learn directly into the roadmap and eval sets
- Prioritize the backlog against broker value, technical feasibility, and quality risk, and run it from concept through launch and iteration
- Define what "good enough" means: build and maintain the eval sets and quality bar each AI skill ships against, and review regressions before every release
- Decide deterministic vs LLM per skill. Know when a rule-based engine beats a model (our next-step recommender is a deterministic engine, not the LLM guessing)
- Own prompt, context, and retrieval design and improve it against measured evaluations rather than gut feel
- Set the guardrails: grounding in real records, permission-scoping, confirm-before-action, hallucination controls, and the rollback plan for non-deterministic failures
- Turn broker workflows into skill specs an engineer can build from: trigger, what it reads, what it writes, guardrail, surface
- Ask sharp questions and unblock engineering
- Measure dual metrics: product outcomes (adoption, task success) and model quality (accuracy, groundedness, regression rate). Watch latency and cost against quality
Requirements:
- 5+ years in product management, including 1 to 2 AI/ML or LLM-powered features shipped to real users
- Hands-on experience with rapid prototyping tools (Claude, Cursor, Replit)
- Comfort with prompt and context engineering, retrieval-augmented generation RAG, plus a practical grasp of what LLMs can and cannot do
- Strong product discovery skills, including customer interviews, problem validation, and translating insights into roadmap priorities
- Experience partnering closely with Engineering and Design to ship high-quality software in a fast-paced environment
- Enough technical depth to trade off model, data, and latency with engineers
- Clear communication to technical and non-technical audiences, and comfort with ambiguity and probabilistic outcomes
- Bonus if you have CRE, proptech, or vertical SaaS experience
- Bonus if you've built assistants, copilots, or agentic products before