About the roleAs Principal PM for the Agentic Platform, you will be the technical product leader for how Zillow's teams build and ship AI agents on a shared platform. You will work as part of the Product AI team alongside fellow product managers, platform engineers, and scientists, and partner closely with Core Tech. You will act as the connecting layer between the core agent platform, our data platforms, and experience teams across consumer shopping, seller, rentals, agent and pro tools, and mortgage.
This is an individual contributor role reporting to the leader of Product AI. Your impact comes through influence, technical credibility, and shaping a platform so powerful and capable that teams can build experiences on it they could never build alone.
What You'll Own
Agentic enablement covers everything a team needs to go from idea to a production agent. You will shape the technical product direction of the platform, with a focus on:
- Contracts, registry, and gateway: how agents, tools, and context sources are registered, discovered, and governed, with contract adherence checked at the edge rather than enforced through central control
- Developer experience: paved paths, reference integrations, and onboarding that cut time-to-first-agent for a new team
- Context and memory: how user and domain context is captured, curated, and delivered into agent context windows, with privacy and user controls built in
- Harness, orchestration, and evals: working with fellow PMs and engineers so the shared agent runtime and quality standards fit together and hold up across the whole customer experience
- You will do this in close partnership with fellow product managers, engineers, and scientists, so that these pieces fit together into one coherent platform and one coherent customer experience.
What You'll Do
- Shape the platform roadmap with fellow PMs, engineering, and science partners, translating product and customer needs into clear technical requirements the platform can build against
- Run a proving-team operating model: onboard 2-3 flagship experience teams, define graduation criteria, then scale to the next wave
- Make the open architecture decisions and get them closed, each with a named decider and a date
- Turn cross-org dependencies into explicit commitments: named owners on both sides, capacity range, re-plan date, and exit criteria
- Bridge traditional engineering and agentic science and data needs, helping teams work through "source of truth" debates, one-way-door schema decisions, facts versus inferences, and the hill-climbing process
- Define and instrument platform success: reuse, time-to-first-agent, cost per team, and coherence of the experience across surfaces
- Keep a clear "what we're not building" list and share it openly with experience teams
This role has been categorized as a Remote position. "Remote" employees do not have a permanent corporate office workplace and, instead, work from a physical location of their choice, which must be identified to the Company. U.S. employees may live in any of the 50 United States, with limited exceptions.
In California, Connecticut, Maryland, Massachusetts, New Jersey, New York, Washington state, and Washington DC the standard base pay range for this role is $195,600.00 - $312,400.00 annually. This base pay range is specific to these locations and may not be applicable to other locations.In Colorado, Hawaii, Illinois, Maine, Minnesota, Nevada, Ohio, Rhode Island, Vermont, and Virginia the standard base pay range for this role is $185,800.00 - $296,800.00 annually. The base pay range is specific to these locations and may not be applicable to other locations.
In addition to a competitive base salary this position is also eligible for equity awards based on factors such as experience, performance and location. Actual amounts will vary depending on experience, performance and location. Employees in this role will not be paid below the salary threshold for exempt employees in the state where they reside.
Who you are- Bachelor's degree in Computer Science, Computer Engineering, Data Science, or a related technical field.
- 10+ years in product management, including platform or infrastructure products whose customers were other product and engineering teams
- Hands-on depth with LLM and agentic systems: orchestration, context engineering, memory and RAG, and eval design
- A track record of driving adoption through influence across organizations with different incentives and roadmaps
- The ability to write concise, compelling, decision-forcing docs at SVP level, then run the execution beneath them
- Comfort with ambiguity and contested ownership. You settle scope disputes by redrawing the boundary, not by escalating
- The human touch to get the right people in a room across engineering, science, and domain teams, and turn differing viewpoints into better decisions
Nice to Have- Data mesh or federated data platform experience
- Experience with experimentation and A/B testing on AI features
- Consumer marketplace or two-sided (consumer plus professional) product experience
