Senior Product Manager, Agentic Platform
פורסם 28 ביולי · 0 מועמדים
התפקיד במילים פשוטות
התפקיד כולל הובלה מקצה לקצה של חלקים מרכזיים בפלטפורמת סוכני ה-AI של החברה, מהתשתיות הבסיסיות ועד להגדרת והפעלת סוכנים בארגונים. ביומיום, העבודה כוללת מחקר, כתיבת אפיונים (specs), בניית אבות-טיפוס באופן עצמאי, והחלטה על סדרי העדיפויות לפיתוח עד לשלב ההשקה.
- Strong product and operational judgment, and product taste you can defend
- Hands-on with LLMs and agentic tools in daily work (Claude, Cursor, n8n, Replit, Lovable, or similar)
- Real intuition for agentic systems: prompting, context, tool use, evals
- Comfort with data models and technical range to read code, query data, and build prototypes
- Extreme speed, clarity, curiosity, and comfort operating without heavy process
- Enterprise SaaS or systems-of-record background
- Shipped a 0→1 product to market
חולץ מתיאור המשרה · מתעדכן אוטומטית
למי זה מתאים
התפקיד מתאים למנהלי מוצר טכניים ועצמאיים עם ניסיון מעשי בכלי AI, מודלים של נתונים ומערכות מבוססות סוכנים, שאוהבים קצב מהיר. הוא פחות מתאים למי שמחפש מפת דרכים מוגדרת מראש, תהליכים מובנים וכבדים, או הסתמכות על הנחיות מוכתבות.
תיאור המשרה המלא
המשרה המקורית · נשמר לעיוןGloat is building the AI-native platform for HR, where agents do the work that used to live in tickets, forms, and endless screens. We act as a small team building a category creation product, and you'll work directly with the founders on what it becomes. How we work • Impact, not job titles. No task is above or beneath anyone. You'll do the research, write the spec, and stand up the prototype yourself. • AI-first, for real. We build with AI across the whole company - not as a talking point, as the way we work. • The best idea wins. Not the loudest voice, not the most senior one. Bring conviction and evidence. • Small teams, high leverage. You'll decide what we build next, why, and in what order - then drive it to ship. The role You'll own a core part of the platform end to end - from the primitives our customers build on to the experience of configuring and running agents inside a live enterprise. You'll have a lot of ownership while staying in the details day to day. You'll succeed here if: • You build and work with AI tools yourself and can speak concretely about where they're strong and where they break. • You think in systems and data models, not screens - you get why the underlying record and data matters more than the UI on top of it. • You have real opinions about how agents should behave in production, and the judgment to know when a slick demo won't survive contact with a real customer. • You move fast, make tradeoffs explicit, and are comfortable making informed calls without perfect information.
Requirements: What we're looking for • Strong product and operational judgment, and product taste you can defend. • Hands-on with LLMs and agentic tools in your daily work (Claude, Cursor, n8n, Replit, Lovable, or similar). • Real intuition for agentic systems: prompting, context, tool use, evals. • Comfort with data models and enough technical range to read code, query data, and build your own prototypes. • Extreme speed and clarity. Shameless curiosity. Allergic to unnecessary process. Nice to have • HR tech, enterprise SaaS, or systems-of-record background. • Shipped a 0→1 product to market. This is an intense environment, and we think intensity and balance can coexist - we don't confuse being busy with being effective, and we care about doing this for the long haul. But we're a small team defining a category in a fast-moving space, and we move quickly. If you want a fully-scoped roadmap handed to you and heavy process to lean on, this won't be the fit. If you want to build the thing that doesn't exist yet, it might be.
שאלות על המשרה
- המשרה לא ציינה שכר. אנחנו מציגים שכר רק כשהמעסיק מפרסם אותו.
- היברידי
- Strong product and operational judgment, and product taste you can defend, Hands-on with LLMs and agentic tools in daily work (Claude, Cursor, n8n, Replit, Lovable, or similar), Real intuition for agentic systems: prompting, context, tool use, evals, Comfort with data models and technical range to read code, query data, and build prototypes, Extreme speed, clarity, curiosity, and comfort operating without heavy process