# Senior Value Engineer - Manufacturing

**Company:** [Celonis](https://hotfix.jobs/companies/celonis)
**Location:** Raleigh, NC
**Role:** Solutions Architecture
**Experience:** 4+ years
**Skills:** Python, SQL, SAP, Oracle, AWS, Azure, GCP, BI Tools, Rpa, Process Mining
**Posted:** 2026-06-17

> Senior Value Engineer serving as trusted advisor for manufacturing customers, leading technical pre-sales discovery through post-sales implementation to drive Process Intelligence Platform adoption and ROI. Requires 4+ years in technical pre-sales or solution engineering with deep manufacturing domain expertise.

## Job Description

## Key Responsibilities

### Manufacturing Solutioning & Value Framing (Pre-Sales)
- Discover and translate the strategic priorities of manufacturing customers into high-impact use cases
- Build highly technical demos, prototypes, and business cases targeted at solving business-critical challenges across:
  - **Idea to Offer**: Accelerating time to market, reducing material costs, and increasing engineering productivity
  - **Supply Chain & Production**: Increasing shopfloor and inventory efficiency, rapidly reacting to short-term supply chain disruptions, and accelerating production ramp-up
  - **Quality & Warranty**: Identifying quality problems before they multiply, freeing up warranty reserves, and accelerating error correction processes

### Proof-of-Value (POV) Execution
- Lead end-to-end POVs, technical discovery, and value workshops in partnership with internal Applied VE teams
- Communicate technical architecture, value opportunities, and strategic roadmaps to C-suite and operational leaders

### Post-Sales Technical Guidance & Account Management
- Seamlessly transition from pre-sales to post-sales
- Partner closely with internal Services and external Partner teams to drive implementations
- Provide AI, solution, and technical guidance needed to build high-value architectures that meet adoption and ROI thresholds

### Scale Value & Drive Expansion
- Define and share best practices for client operating models and governance
- Drive enterprise-wide adoption and value realization
- Lead QBRs and design strategic expansion roadmaps aligned with the client's operational realities

### Process Transformation & AI Enablement
- Use process intelligence to feed operational context to AI and LLM tools
- Help clients move from simple rule-based automation to intelligent, agentic systems within their production and supply chain environments

### Domain Leadership
- Serve as the internal and external technical subject matter expert for the Manufacturing vertical
- Bridge the gap between IT and OT systems
- Provide product feedback to development teams based on emerging industry use cases

## Qualifications & Requirements

### Experience
- 4+ years of experience in technical pre-sales, solution engineering, or highly technical customer success roles
- Proven track record of staying deeply involved post-sale to drive project implementations and manage enterprise accounts

### Business Process Knowledge
- Native understanding of manufacturing business processes
- In-depth experience in domains such as Supply Chain Operations, Production/Shopfloor Management, Quality Assurance, or Product Lifecycle Management (PLM)
- Ability to map complex operational bottlenecks to technical solutions

### Technical Skills
- Solid knowledge of Python and/or SQL
- Strong familiarity with major Business Software/ERP applications prevalent in manufacturing (e.g., SAP, Oracle)
- Experience with cloud platforms (AWS, Azure, GCP)
- Experience with BI tools, RPA, and building data-driven dashboards and automations

### Project & Stakeholder Management
- Exceptional capability to manage multiple, complex projects simultaneously across aligned accounts at various stages of the value journey
- Proven ability to present and communicate effectively to VP+ and C-suite stakeholders

### Education
- Bachelor's degree required
- Focus in computer science, engineering, mathematics, supply chain management, or a related field is preferred

## Nice to Have
- Hands-on experience building agentic systems using LLM orchestration, RAG, function calling, prompt engineering, and common ML libraries (LangChain, pandas, PyTorch)
- Familiarity with IT/OT convergence and industrial IoT data structures

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