Das ist der Job
Translate business requirements into clear epics, user stories, and acceptance criteria for engineering.
Darum lohnt es sich
Responsibilities Own the AI product roadmap for GTM apps team, aligned with business OKRs and AI strategy. Partner with data and analytics teams to ensure GTM data is AI‑ready: clean, structured, and access‑governed. Experience working in Agile/Scrum environments with cross‑functional engineering teams.
Identify AI opportunities in Lead-to-Cash and customer Success processes by driving business workshops, ideation sessions and executive meetings. Define, prioritize, and groom the backlog for agentic workflows (autonomous agents, AI assisted workflows and LLM integrations) across sales, marketing, and customer success platforms.
Make effective build vs buy decisions on agentic capabilities in a complex applications environment. Partner with business to define and track AI-specific KPIs: model accuracy, agent task completion rate, hallucination rate, business ROI, data privacy compliance, fairness reviews, and responsible use policies.
Design and champion prompt engineering standards and context-window optimization strategies across GTM features. Evangelize AI‑first product thinking and drive AI adoption metrics across the GTM IT organization. Embrace agentic AI and LLM‑powered tooling as a core part of your practice.
Stay current with rapidly evolving AI/ML technologies and apply them pragmatically to GTM systems. Champion automation‑first thinking – if it can be agentic, make it agentic.
Requirements Bachelor's degree in Business, Computer Science, Information Systems, or related field. 8+ years of product management experience, with at least 2 years in enterprise SaaS or GTM technology with focus on AI. Proven track record delivering AI or automation products end‑to‑end.
Strong understanding of GTM business processes: Lead‑to‑Cash, CPQ, CRM, Marketing Automation. Hands‑on familiarity with agentic AI, LLMs, or AI workflow platforms. Working knowledge of RAG architecture, prompt engineering patterns, and LLM API capabilities (OpenAI, Anthropic, AWS Bedrock, SaaS Agents).
Comfort operating under uncertainty – AI features are probabilistic, not deterministic. #J-18808-Ljbffr
