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Salary: USD 200,000 - 255,000 / annual
Sprig is an AI-powered customer survey platform used by leading companies like Microsoft, DoorDash, Notion, Figma, Coinbase, and TripAdvisor. The platform modernizes customer research by using AI agents to design studies, adapt surveys in real time, and deliver actionable insights in hours instead of weeks.
You will own the survey capabilities and workflows at the heart of Sprig as a Lead Product Manager, Core. Your scope spans survey creation (including advanced logic and question types), distribution channels (panels, email, and others), and enterprise capabilities (permissions, integrations, survey management). You'll expand what customers can accomplish while making sophisticated workflows intuitive and reliable.
This is a hands-on individual contributor role reporting directly to the CEO. You'll partner closely with engineering, design, fellow product managers, and go-to-market teams to set direction for your product area, combining customer research, usage data, and competitive insight to identify valuable problems. You'll work directly with enterprise customers to understand workflows and validate solutions, make decisive tradeoffs between customer commitments and product differentiation, and lead execution from discovery through launch. You'll define success metrics before development, partner on go-to-market rollout, and use adoption data to improve shipped products.
The role requires four days per week in the downtown San Francisco office (near Montgomery BART). Sprig is backed by $85M from Andreessen Horowitz, Accel, and First Round Capital and was recently recognized by Fortune as a top 50 best place to work in the US.
REQUIREMENTS:
- 7+ years of product management experience, including ownership of B2B SaaS products from discovery through launch and adoption
- Experience shipping enterprise capabilities that measurably improved adoption, supported expansion, or strengthened retention; ability to explain the customer problem, your contribution, and results
- Track record of leading ambiguous initiatives with limited day-to-day guidance; demonstrated ability to make consequential prioritization decisions, resolve cross-functional dependencies, and deliver results
- Evidence of simplifying complex workflows through partnership with design and engineering; use of customer feedback or usage data to demonstrate improvement
- Clear communication and constructive leadership; ability to explain decisions and tradeoffs, build alignment across functions, and challenge assumptions with evidence
- Fluency in customer research and product analytics; ability to use qualitative and quantitative evidence to identify opportunities, test assumptions, and assess release outcomes
- Practical AI fluency; ability to use AI tools to accelerate work and evaluate where AI improves customer experience, including tradeoffs around accuracy, trust, and user control
- Experience making product decisions under technical constraints; ability to point to tradeoffs made with engineers to reduce scope, resolve dependencies, or improve reliability
- Plus: experience shipping AI-powered products, research tools, or products at a growing startup
