Senior Product Manager - AI Migrations

Responsibilities

• Own Feature Direction & Alignment: Provide clarity, conviction, and insight for owned features. Ensure roadmap and projects align with broader company strategy and migration goals.
• Balance Technical Constraints: Deeply understand customer migration needs (data types, ETL pipelines, post-migration validation). Weave technical constraints into product decisions, balancing engineering effort, customer value, and feasibility.
• Execute with Transparency: Help engineering team prioritize effectively, explaining rationale behind technical trade-offs. Keep cross-functional stakeholders updated on status with precise, succinct communication.
• Drive with an MVP Mindset: Partner with engineering to foster high-velocity culture focused on speed and unblocking customer pipelines. Define and ship MVPs to select customers to validate core hypotheses and iterate based on real-world feedback.
• Understand GTM & Enablement: Learn how migration features are taken to market. Understand required collateral, enablement pathways, and partner ecosystems (Professional Services and GSIs).
• Analyze Metrics & Insights: Track usage and health metrics. Conduct regular data analysis to deliver insights and make data-driven decisions that push north star metric: reducing overall customer migration time.
• Contribute to the Team Culture: Act as a mentor, help solve team-wide issues (quality or process optimization), and participate as interviewer to scale the PM organization.

Requirements

• 6+ years of enterprise product management experience, with proven track record of independently running features through the full product lifecycle.
• Solid technical foundation: Strong familiarity with data ecosystems (databases, SQL platforms, data engineering, ETL workloads) and ability to factor technical limitations into feature design.
• Developer/Partner focus: Experience building or working with developer tools, APIs, or data platforms where user ergonomics and clarity are critical.
• GenAI / LLM familiarity: Practical exposure to or strong understanding of delivering AI-powered features (e.g., code translation, developer co-pilots, semantic validation, or working with frameworks like LangChain).
• Strong collaboration skills: Ability to build relationships across functions (Engineering, Professional Services, Partners) and leverage direct and indirect influence.