Solutions Engineer

Shelf

United States

Remote

USD 140,000 - 190,000

Full time

14 days+

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Benefits offered by this job

Comprehensive health and wellness packages
Team-wide aligned values and goals
Realistic expectations

Job summary

A leading technology firm is hiring a Solutions Engineer to independently lead proof-of-value pilot engagements with enterprise clients. The role requires strong data modeling and communication skills, with a focus on driving sales success through technical expertise. Ideal candidates should have over 7 years in customer-facing technical roles, proficient in Python and AI tools. This position is remote within the United States with some travel required to meet clients and attend events.

Qualifications

  • 7-10+ years in technical pre-sales, data engineering, or solutions architecture.
  • Strong expertise in data modeling and data platforms.
  • Experience with knowledge graphs and semantic technologies preferred.
  • Proficiency in scripting and automation; Python preferred.
  • Hands‑on with AI coding tools; cloud architectures (AWS/Azure/GCP).
  • Proven customer‑facing impact with enterprise sales awareness.

Responsibilities

  • Lead independent POV engagements with enterprise prospects.
  • Design custom ontologies and configure solutions.
  • Conduct technical discovery and present solutions.
  • Support Account Executives through technical evaluation phases.
  • Collaborate with Engineering on challenges during POVs.
  • Drive engagement through deal closing and onboarding.
  • Support land-and-expand opportunities with customers.

Skills

Data modeling
ETL/pipeline expertise
Python scripting
Customer communication
Technical problem solving
Sales orientation
Python scripting
Automation
AI coding tools
Cloud architectures (AWS/Azure/GCP)
Enterprise sales support
Communication skills
Presentation skills

Education

Bachelor’s degree in Computer Science, Engineering, Data Science, or related field

Tools

AI coding tools (Claude Code, Cursor, GitHub Copilot)
Cloud architectures (AWS, Azure, GCP)
GCP
Claude Code
Cursor
GitHub Copilot

Job description

Solutions Engineer

We’re unlocking community knowledge in a new way. Experts add insights directly into each article, started with the help of AI.

Overview

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.

Job Description

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.

What We’re Looking For
  • 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.
Key Responsibilities
  • 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.
Qualifications
  • 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, 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 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.
Success Metrics
  • 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 timeframes.
  • ARR Growth Contribution – Support overall company ARR growth through new customer acquisition and existing account expansion.
  • Technical Quality – Consistently deliver well‑designed ontologies and technical solutions that meet customer requirements.
What We Offer
  • Realistic, clearly communicated expectations.
  • Team‑wide aligned values and goals.
  • Comprehensive health and wellness packages.
Location

Remote within the United States with flexibility for 50% travel for high‑stakes customer meetings, industry events, and internal leadership meetings.

Why Shelf
  • GenAI will be at least a $18 Trillion market by 2032, and Shelf is a core infrastructure that enables GenAI to be deployed at scale.
  • We are blazing the path for the future of Artificial Intelligence globally.
  • Our Leadership Team has deep AI domain expertise and enterprise SaaS background to execute this plan.
  • We love our customers…and they love us because of our innovative capabilities, rock‑solid reliability, and the improvements they see in their business KPIs.
  • We have raised over $60 million in funding; our investors include Insight Partners, Tiger Global, Base10, and others.
  • We have high‑velocity growth powered by the most innovative product in our category.
  • We now have over 100 employees across multiple U.S. states and European countries, and we have ambitious hiring goals over the next few quarters.
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