Sales Engineer German skills

The Sales Engineer will serve as a forward-deployed technical expert, independently leading proof-of-value engagements with enterprise prospects. This role combines deep technical expertise in data modeling and ontology design with hands-on implementation skills to deliver rapid-cycle pilots that demonstrate Shelf's value and convert to closed deals.This is a unique opportunity to work at the cutting edge of AI and data quality, designing custom data models and configuring reasoning agents to solve complex enterprise challenges. You'll operate with significant autonomy, embedded with prospects during 3-5 day pilots, iterating quickly to prove measurable value. Your ability to understand customer data architectures, design semantic models, and deliver technical solutions will be crucial to our sales success.Reporting to the Field CTO, you'll partner with Account Executives throughout the sales cycle, with primary responsibility during technical evaluation and POV phases. Beyond new customer acquisition, you'll support expansion opportunities within existing accounts, contributing to our land-and-expand growth strategy. You'll work directly alongside Engineering during POVs and collaborate on building reusable templates and best practices.The ideal candidate brings 5-10 years of experience combining technical depth in data platforms and modeling with customer-facing skills. As a self-starter, you'll quickly ramp through hands-on internal projects that mirror customer engagements. You're comfortable writing scripts, leveraging AI coding tools like Claude Code, and delivering approximately 8-10 POVs per quarter. Experience with knowledge graphs, ontologies, or semantic technologies is strongly preferred, though exceptional data modeling expertise can substitute.What we are looking for:Technical Depth - Strong data modeling, data platforms, and ETL/pipeline expertise; knowledge graphs and ontologies experience strongly preferredForward-Deployed Engineer - Comfortable operating independently with prospects, leading technical engagements with minimal supervisionTechnical Problem Solver - Writes Python scripts, automates workflows, and leverages AI coding tools to rapidly build and iterate solutions during customer engagementsCustomer-Facing Excellence - Exceptional communication skills with technical and business stakeholders; comfortable presenting and iterating with customersRapid Execution - Thrives in fast-paced 3-5 day pilot cycles; delivers value quickly and iterates based on feedbackSales-Oriented Mindset - Understands enterprise sales cycles and is motivated by converting POVs to closed dealsContinuous Learner - Stays current with AI/GenAI trends, data technologies, and modern engineering practicesResponsibilitiesLead independent POV engagements with enterprise prospects, designing custom ontologies and configuring solutions within 3-5 day cyclesConduct technical discovery and present solutions to Data Engineers, Enterprise Architects, and AI/ML EngineersSupport Account Executives throughout sales cycles with primary ownership during technical evaluation and POV phasesWork directly with Engineering on technical challenges and custom implementations during POVsContinue engagement through deal closing and initial customer onboarding alongside Customer SuccessSupport existing customer expansion opportunities as part of land-and-expand strategyCollaborate with Field CTO to build reusable ontology templates and POV best practicesRequirements5-10 years in technical pre-sales, data engineering, solutions architecture, or similar customer-facing technical rolesStrong expertise in data modeling, data platforms, and ETL/data pipelinesExperience with knowledge graphs, ontologies, or semantic technologies strongly preferredProficiency in scripting and automation (Python preferred)Hands-on experience with AI coding tools (Claude Code, Cursor, GitHub Copilot, etc.)Deep understanding of enterprise data platforms and cloud architectures (AWS, Azure, GCP)Proven track record in customer-facing technical roles with demonstrated sales impactExceptional presentation and communication skills with technical and business audiencesStrong English and German verbal and written communicationBachelor's degree in Computer Science, Engineering, Data Science, or related fieldExperience in B2B SaaS, AI/ML, or data quality solutions preferredSuccess Metrics To be successful in this role, you should aim to achieve the following within the first 18 months:POV Conversion Rate - Achieve 70%+ conversion rate from pilot to closed dealPOV Delivery Volume - Successfully deliver 8-10 high-quality POVs per quarter within 3-5 day timeframesARR Growth Contribution - Support overall company ARR growth through new customer acquisition and existing account expansionTechnical Quality - Consistently deliver well-designed ontologies and technical solutions that meet customer requirementsWhat Shelf Offers:Competitive salary, equity, & benefitsRealistic, clearly communicated expectationsTeam-wide aligned values and goalsComprehensive health packageHardware: MacBook Pro.Why Shelf:GenAI will be at least a $4 Trillion market by 2032 and Shelf is a core infrastructure that enables GenAI to be deployed at scaleOur Leadership Team has deep knowledge management and AI domain expertise and enterprise SaaS background to execute this planWe've been helping our customers prevent knowledge mismanagement since our founding in 2017We have raised over $60 million in funding and our investors include Tiger Global, Insight Partners, Connecticut Innovations, and othersWe have high velocity growth powered by the most innovative product in our category, 3X growth for 3 years in a rowWe now have over 100 employees in multiple U.S. states and European countries, and we have ambitious hiring goals over the next few monthsAbout ShelfThere is no AI Strategy without a Data Strategy. Getting GenAI to work is mission critical for most companies but 90% of AI projects haven't deployed. Why? Poor data quality - it is the #1 obstacle companies have in getting GenAI projects into production.We've helped some of the best brands like Amazon, Mayo Clinic, AmFam, and Nespresso solve their data issues and deploy their AI strategy with Day 1 ROI.Simply put, Shelf unlocks AI readiness. We provide the core infrastructure that enables GenAI to be deployed at scale. We help companies deliver more accurate GenAI answers by eliminating bad data in documents and files before they go into an LLM and create bad answers.Shelf is partnered with Microsoft, Salesforce, Snowflake, Databricks, OpenAI and other big tech players who are bringing GenAI to the enterprise.Our mission is to empower humanity with better answers everywhere.