Senior Product Manager - Sequoia

First American•Santa Ana, CA

2d•$129,300 - $172,300•Remote

About The Position

We are looking for an experienced, hands-on Senior Product Manager who thrives in ambiguity and enjoys solving complex business problems through AI enabled software. You will lead one of Sequoia’s highest priority product initiatives, partnering closely with Engineering, Operations, Underwriting, Data Science, and Design to deliver measurable business outcomes. This role is ideal for a product leader who enjoys working deeply with cross functional teams to define product strategy, translate ambiguous business problems into clear product requirements, and lead AI product development from concept through launch and continuous improvement. As priorities evolve, you may lead different key initiatives, giving you the opportunity to solve some of the organization’s most important product challenges. We are building a modern product organization that values curiosity, data driven decision making, rapid learning, experimentation, and continuous improvement. We are looking for people who challenge assumptions, think creatively, and help a large organization operate with greater speed and agility. This is a remote position open to candidates located in the United States. Candidates must be able to work within time zones from Pacific through Eastern to support collaboration across distributed teams. Quarterly travel to Southern California is expected.

Requirements

8+ years of software or technology product management experience, or an equivalent combination of experience and demonstrated impact, leading complex software products.
Demonstrated ability to translate ambiguous business problems into clear, actionable product requirements.
Experience writing high quality PRDs, user stories, acceptance criteria, and other product documentation for engineering teams.
Experience partnering closely with engineering teams throughout discovery, development, launch, and post launch improvement.
Strong data fluency and a track record of using qualitative and quantitative evidence to identify opportunities, estimate impact, test assumptions, prioritize work, and measure results after launch.
Experience with AI product development practices, including truth data, evaluations, experimentation, and iterative quality improvement.
Exceptional written and verbal communication skills across technical teams, business stakeholders, and executive audiences.
Demonstrated ability to influence cross functional teams and drive alignment without direct authority.
Highly curious and growth oriented, with the ability to quickly learn complex business domains, emerging technologies, and customer workflows.
Comfortable operating in ambiguous, fast moving environments; willing to challenge assumptions, think creatively, and find practical paths forward.

Nice To Haves

Experience developing AI enabled or machine learning products, including LLM based applications or human in loop workflows.
Experience in title production is a strong plus; related experience in mortgage, real estate, insurance, fintech, or another regulated and operationally complex domain is also valuable.
Experience scaling enterprise software across products, markets, geographies, or business units.

Responsibilities

Own product strategy, roadmap, and execution for one of Sequoia’s highest priority initiatives.
Partner closely with Engineering, Operations, Underwriting, Data Science, and Design to understand complex business problems and transform them into clear product direction.
Develop high-quality product requirements, PRDs, user stories, acceptance criteria, and supporting documentation that enable engineering teams to execute with confidence.
Exercise sound product judgment by making timely decisions, clarifying tradeoffs, and transforming ambiguous business problems into clear, testable product requirements.
Partner with engineering throughout implementation by answering questions, refining requirements, resolving edge cases, and making product decisions that keep development moving.
Partner with AI engineers and data scientists to define truth data, evaluation frameworks, experimentation strategies, and iterative AI product development practices that improve product quality and business outcomes.
Use qualitative and quantitative data to identify opportunities, estimate potential impact, prioritize investments, and measure realized impact after launch.
Balance customer value, business impact, technical feasibility, quality, and implementation risk when making product tradeoffs.
Communicate product strategy, roadmap, progress, decisions, and outcomes to executive leaders and cross functional stakeholders.
Coordinate across teams to manage dependencies, resolve blockers, and deliver cohesive outcomes.