SlipstreamJobs tracks this role from the company's public career site. Apply directly on the employer's site.
Superhuman (formerly Grammarly, now a multi-product AI platform) is seeking a Senior Product Manager to own the core data platform and shared data services powering its suite of products including Grammarly, Coda, Mail, and Go. This is a technical, high-leverage role focused on making data complexity simple for both customers and internal teams.
You will define how Superhuman understands users, teams, organizations, permissions, content, activity, and product interactions across a growing suite of applications. Your core responsibility is turning messy, distributed data into trusted platform primitives that product and AI teams can confidently build upon. You'll partner closely with data engineering, product engineering, data science, security, and cross-functional product teams to design shared services, schemas, governance patterns, and interfaces that are durable, scalable, and user-friendly.
Key responsibilities include: owning the roadmap for the core data model and shared platform services; defining canonical entities, relationships, events, permissions, and semantics; partnering with engineering to build reliable, scalable data systems and APIs; working across product teams to understand data needs and drive consistency; establishing product-quality standards for data trust, documentation, governance, and developer experience; and defining success metrics to communicate platform impact.
You should have 5+ years in product management with meaningful experience owning technical platform, data, infrastructure, or AI-enabling products. Hands-on fluency with data systems is essential—including data modeling, schemas, event systems, APIs, warehouses, and analytics infrastructure. You're comfortable with technical tradeoffs, architecture, reliability, privacy, security, and scale. You can translate complex platform capabilities into clear requirements and adoption paths for internal teams, and you have experience shipping products serving multiple teams or surfaces at scale.
The ideal candidate thinks in systems, metrics, models, and pipelines; understands that internal platforms win through trust and usability, not just technical elegance; cares deeply about data semantics and governance; empathizes with enterprise expectations around privacy and compliance; embeds AI into daily workflows; takes extreme ownership; and operates with low ego and results-driven focus. The role offers a hybrid working model balancing focus time with in-person collaboration.
