Lead Applied Value Engineer - High Tech

Celonis

Location not specified

Full Time

Posted September 17, 2026

$196k - $230k

Climate Technology

Apply Now

Application opens on company website

Job Description

At Celonis, we believe our people make us who we are and that “The Best Team Wins”.

Key Responsibilities

AI Discovery & Solutioning: Understand customers' AI strategies and sector-specific challenges (e.g., demand forecasting, out-of-stock prevention, shelf placement, trade spend analytics). Find the best problem-solution fit and translate business requirements into innovative, needle-moving solutions.
Pre- and Post-Sales Execution: Drive the full customer lifecycle. Lead technical discovery and capability demonstrations during pre-sales, and remain deeply involved post-sale to guide implementation and ensure agreed value and adoption thresholds are met.
Hackathons & Prototyping: Leverage cutting-edge AI technologies to rapidly build creative prototypes during customer hackathons. Solve critical pain points specific to inventory routing, fulfillment, and promotional alignment with a proactive, "can-do" approach.
Agentic Process Transformation: Shift customers from traditional, rule-based automation to autonomous AI agents empowered by Process Intelligence (e.g., autonomous inventory replenishment, intelligent deduction management), ensuring real ROI on AI deployments.
Proof Projects: Architect and execute business-critical Proof-of-Value projects. Deliver secure, scalable LLM/agent systems with RAG, tools, and guardrails, integrating seamlessly with enterprise retail data, identity protocols, and consumer data privacy frameworks.
Domain & Industry Leadership: Serve as the primary technical subject matter expert for the High Tech sector. Scale deep domain expertise across the organization to deliver high-value solutions for global brands, mega-retailers, and distribution partners.
Smart Warehouse & Fulfillment Operations: Champion modern distribution initiatives. Specialize in warehouse management system (WMS) optimization, RFID inventory tracking, micro-fulfillment centers, dynamic order routing, and fulfillment center workflows for high-velocity retail operations.
Omnichannel & DTC Transformation: Act as a technical advisor on the transition to seamless omnichannel and Direct-to-Consumer (DTC) execution. Optimize order-to-cash cycles, customer returns processing, dynamic pricing models, and loyalty program integrations.
Sustainable Supply Chain & Eco-Fulfillment: Drive technical strategy for sustainable retail operations. Focus on tracking Scope 3 emissions, optimizing cold-chain efficiency, reducing perishable food waste, and streamlining sustainable packaging workflows across the distribution network.

Requirements

Experience: 8+ years leading end-to-end technical pre-sales and post-sales engagements within the CPG, retail, or e-commerce space. Proven ability to define AI roadmaps, build compelling ROI/TCO business cases, and guide technical implementations to value realization.
Domain Expertise: Deep understanding of the High Tech business processes. In-depth experience in domains such as Inventory Management, Supply Chain, Trade Promotion, Category Management, or Loss Prevention, with the ability to translate strategic requirements into impactful solutions.
Technical Proficiency: Solid knowledge of Python and common ML libraries (LangChain, pandas, pydantic, sklearn, PyTorch), as well as data engineering tools relevant to handling large-scale POS, transactional, and inventory data.
Communication Skills: Strong presentation and storytelling skills for both internal and external stakeholders (C-level executives, VPs of Merchandising, and Supply Chain Leaders), capable of leading technical whiteboarding sessions, formal readouts, and live demos.
Education: Bachelor’s Degree required; Master's Degree in computer science, business analytics, engineering, mathematics, or a related field (or equivalent work experience) preferred.
Agentic Systems: Hands-on experience building agentic systems using LLM orchestration, RAG, function calling, and prompt engineering, with rigorous evaluations for enterprise consumer environments.
LLM Ecosystem: Working knowledge of OSS packages like LangChain or LlamaIndex.
Cloud & Enterprise Stack: Experience deploying and monitoring models at scale across major cloud platforms (AWS Bedrock, Azure AI, GCP Vertex) and familiarity with enterprise data structures (SAP, Salesforce Commerce Cloud, Snowflake, POS formats).
Generative AI: Expertise in GenAI techniques (RAG, few-shot learning, multi-agent orchestration, multimodal understanding) to build high-impact use cases like automated customer service workflows, intelligent product catalog enrichment, or automated promotion generation.
Sponsorship is not available for this role.
The base salary range below is for the role in the specified location, based on a Full Time Schedule. Total compensation package will include base salary + bonus/commission + equity + benefits (health, dental, life, 401k, and paid time off). Please note that the base salary range is a guideline, and that the actual total compensation offer will be determined based on various factors, including, but not limited to, applicant's qualifications, skills, experiences, and location.
The base salary range below is for the role in New York, based on a Full Time Schedule.
$196,000
—
$230,000 USD