Solutions Engineer

Solutions Engineer

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There is no AI Strategy without a Data Strategy. Getting GenAI to work is mission critical for most companies, yet 90% of AI projects haven’t deployed. Poor data quality is the #1 obstacle in getting GenAI projects into production. Shelf unlocks AI readiness by eliminating bad data before it enters an LLM, enabling more accurate GenAI answers at scale.

Shelf partners with Microsoft, Salesforce, Snowflake, Databricks, OpenAI, and other tech leaders to bring GenAI to the enterprise. Our mission is to empower humanity with better answers everywhere.

The Solutions Engineer is a forward‑deployed technical expert who independently leads proof‑of‑value engagements with enterprise prospects. You will combine 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.

As part of a small, fast‑moving team you’ll work with customers during 3‑5 day pilots, iterating quickly to prove measurable value. You’ll understand customer data architectures, design semantic models, and deliver technical solutions that drive sales success.

• Technical Depth – Strong data modeling, data platforms, and ETL/pipeline expertise; knowledge graphs and ontologies experience strongly preferred.
• Forward‑Deployed Engineer – Comfortable operating independently with prospects and leading technical engagements with minimal supervision.
• Technical Problem Solver – Writes Python scripts, automates workflows, and leverages AI coding tools to rapidly build and iterate solutions during customer engagements.
• Customer‑Facing Excellence – Exceptional communication skills with technical and business stakeholders; comfortable presenting and iterating with customers.
• Rapid Execution – Thrives in fast‑paced 3‑5 day pilot cycles; delivers value quickly and iterates based on feedback.
• Sales‑Oriented Mindset – Understands enterprise sales cycles and is motivated by converting POVs to closed deals.
• Continuous Learner – Stays current with AI/GenAI trends, data technologies, and modern engineering practices.

• Lead independent POV engagements with enterprise prospects, designing custom ontologies and configuring solutions within 3‑5 day cycles.
• Conduct technical discovery and present solutions to Data Engineers, Enterprise Architects, and AI/ML Engineers.
• Support Account Executives throughout sales cycles with primary ownership during technical evaluation and POV phases.
• Work directly with Engineering on technical challenges and custom implementations during POVs.
• Continue engagement through deal closing and initial customer onboarding alongside Customer Success.
• Support existing customer expansion opportunities as part of land‑and‑expand strategy.
• Collaborate with Field CTO to build reusable ontology templates and POV best practices.

• 7‑10+ years in technical pre‑sales, data engineering, solutions architecture, or similar customer‑facing technical roles.
• Strong expertise in data modeling, data platforms, and ETL/data pipelines.
• Experience with knowledge graphs, ontologies, or semantic technologies strongly preferred.
• Proficiency in scripting and automation (Python preferred).
• Hands‑on experience with AI coding tools (Claude Code, Cursor, Git Hub 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 impact.
• Exceptional presentation and communication skills with technical and business audiences.
• Bachelor’s degree in Computer Science, Engineering, Data Science, or related field.
• Experience in B2B SaaS, AI/ML, or data quality solutions preferred.

• POV Conversion Rate – Achieve 70%+ conversion rate from pilot to closed deal.
• POV Delivery Volume – Successfully deliver 8‑10 high‑quality POVs per quarter within 3‑5 day time frames.
• ARR Growth Contribution – Support overall company ARR growth…