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Celonis is seeking a Senior Value Engineer for its Scale Team to drive value, adoption, and customer success across a portfolio of enterprise accounts. This is a trusted advisor role focused on strengthening customer engagement and ensuring long-term success with the Celonis Process Intelligence Platform.
You will serve as a strategic partner to customers and regional partners, responsible for building scalable engagement strategies, identifying expansion opportunities, and mitigating renewal risks. Key responsibilities include establishing Centers of Excellence (CoEs) to enable customer self-sufficiency, orchestrating partner-delivered account work, and managing 1:N programmatic motions such as value bootcamps, sprint initiatives, and innovation deployments.
The role emphasizes efficient, scaled interactions across a diverse portfolio rather than traditional high-touch 1:1 relationships. You will leverage AI-driven tools and copilots to monitor portfolio health, surface renewal risks, track adoption signals, and identify expansion opportunities in parallel across all accounts. You will work with auto-generated programmatic content, including industry briefs and customer-specific presentations, to manage the portfolio efficiently.
You will maintain cross-industry fluency, drive AI-orchestrated account plans leveraging platform best practices, and deploy automated value reports that empower customers to drive their own business outcomes. Collaboration with internal technical teams (CoE and Applied Value Engineers) on complex builds is expected, with your focus on big-picture value realization.
Required qualifications include 3–5 years of programmatic execution experience, proven ability to manage complex products efficiently, and end-to-end post-sales customer journey expertise across a portfolio. You need broad industry and domain expertise with understanding of industry-specific business processes and the ability to identify improvement opportunities. Strong communication skills, stakeholder management capabilities, and comfort with AI-fluent operations are essential.
