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Superhuman (formerly Grammarly, now part of a unified AI productivity platform) is seeking a Senior Product Manager to own the core data platform and shared data services powering its multi-product suite including Docs, Mail, Go, Grammarly, and future products.
In this role, you will define how Superhuman understands users, teams, organizations, permissions, content, activity, signals, and product interactions across its growing ecosystem. You'll transform distributed, messy data into trusted platform primitives that product and AI teams can build on confidently.
Key responsibilities include:
- Owning the roadmap for Superhuman's core data model and shared platform services across multiple products
- Defining canonical entities, relationships, events, permissions, and semantics that product and AI teams depend on
- Partnering with data engineering, product engineering, data science, security, and product teams to design shared services, schemas, governance patterns, and interfaces
- Working across product teams to understand data needs, unblock high-impact use cases, and drive consistency without slowing innovation
- Establishing product-quality standards for data trust, documentation, governance, discoverability, and developer experience
- Defining success metrics, prioritizing investments, and using data to communicate platform impact and adoption
You'll be a technical, high-leverage product leader who loves data systems as much as customer outcomes. The role requires deep partnership with engineers and data practitioners on technical tradeoffs, architecture, reliability, privacy, security, and scale.
Superhuman offers a hybrid working model with flexibility for focus time and in-person collaboration in San Francisco.
QUALIFICATIONS:
- 5+ years in product management with meaningful experience owning technical platform, data, infrastructure, or AI-enabling products
- Hands-on fluency with data systems and platforms, including data modeling, schemas, event systems, APIs, warehouses, or analytics infrastructure
- Comfort working closely with engineers and data practitioners on technical tradeoffs, architecture, reliability, privacy, security, and scale
- Ability to translate complex platform capabilities into clear product requirements, adoption paths, and user experiences for internal product teams
- Experience shipping products or platforms that serve multiple teams, customers, or surfaces at scale
- Demonstrated ability to take ambiguous, cross-functional problems from insight to shipped product with minimal oversight
- Strong analytical rigor, platform product sense, data craft, enterprise empathy, and AI-first operator mindset
- Ability to work independently with minimal guidance, proactively manage tasks and priorities, and thrive in fast-paced, results-driven environments
