Senior Product Manager, AI
About The Position
Buildout is building the Broker Operating System for commercial real estate. You will own the strategy and roadmap for AI, the AI assistant embedded across the suite: the skills it performs, the judgment of when it should use AI reasoning versus the platform's own exact calculations, and the quality bar it ships against. You will also bring AI into the marketing and document creation workflows that made Buildout the leader in commercial real estate, helping brokers build the materials that win and sell listings, so they get to market and pitch faster. You will work day to day with engineering and design.
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.
Nice To Haves
- CRE, proptech, or vertical SaaS experience.
- Built assistants, copilots, or agentic products before.
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.
Benefits
- 2 medical plans to choose from
- 100% coverage of employee dental and vision insurance premiums
- HSA seed
- company-paid STD, LTD, life insurance, and telemedicine
- a wellness benefit of $400/year
- Flexible PTO
- 14 paid company holidays
- paid parental leave
- give back days
- 401(k) with 4% company match and immediate vesting
- monthly remote work reimbursement ($600/year)
- annual, in-person company kickoff
- Challenging problems to solve with a committed and supportive team who are invested in your growth and development
- A wonderfully quirky culture where you’re encouraged to bring your whole self to work
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What This Job Offers
Job Type
Full-time
Career Level
Senior
Education Level
No Education Listed
