Deepsetai - Berlin - Global - Procurement & Supply Chain
We're hiring a Value Engineer to guide public sector customers from first conversation to long-term success. You'll help Sales to qualify and win the right deals, design solutions and services engagements that work in the real world. The objective is to ensure customers reach value quickly, own the coordination of all resources required for value realization, and proactively create opportunities to grow the relationship.
This role is a prescriptive, opinionated authority on which AI use cases make both business and technical sense. You'll develop a structured account thesis from day one and tie every decision back to measurable outcomes.
At deepset, we're on a mission to make custom AI solutions accessible to every organization. With Haystack, thousands of developers build advanced LLM applications every day, while our enterprise-ready AI Platform helps companies turn large language models into business value. We're remote-first, flexible, and built on a culture of trust and ownership. You'll collaborate with top-tier tech talent, tackle meaningful challenges, and help transform complex AI into solutions that are simple, powerful, and ready for the real world.
Lead structured, multi-persona discovery to uncover goals, challenges, KPIs, and decision-making dynamics across all relevant stakeholders; from end users and Line of Business owners to technical architects and executive sponsors.
Identify the full landscape of stakeholder needs; distinguishing between technical requirements, business outcomes, and organizational constraints; being able to adjust pitch, messaging, and solution positioning autonomously per persona.
Act as a sparring partner with Enterprise Sales on deal quality, qualification rigor, and expansion potential, with a shared accountability for revenue closure.
Translate customer needs into clear technical and business solutions, and define the full offering required for the customer to succeed; including scoped services engagements covering effort, team and project structure (including partner involvement if required).
Build demos and POCs that prove value against defined business metrics, not just technical feasibility.
Own AI risk management across project feasibility, data evaluation/readiness and solution adoption.
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