
AI Solutions Architect
Primary stack
Nice to have's
Job description
About the Position
AI Solutions Architect
Location
New York City
Employment Type
Full time
Location Type
On-site
Department
GTMSales
About Shelf
While everyone’s talking about agents, most enterprise AI initiatives fail to reach production because they can’t deliver reliable, deterministic outcomes.
Models and agent frameworks are rapidly becoming commoditized. What’s missing is the data layer: an AI-ready model of a company’s unstructured knowledge that replaces hallucinations with trustworthy answers.
At Shelf, we’ve spent eight years solving the hardest problems in unstructured data and knowledge management. Now, we’re delivering this missing layer for some of the world’s largest companies.
About the Role
As a Solutions Architect at Shelf, you'll be the technical authority behind our most complex customer opportunities, translating enterprise data, architecture, and AI challenges into solutions that can prove value quickly and scale into production.
You'll engage early in the sales cycle, leading technical discovery and conversations around architecture, security, integrations, and deployment strategy. You'll work with senior technical stakeholders to understand their existing data environment and AI initiatives, design the target solution, and guide proof-of-value pilots using real customer data.
This is a highly technical, customer-facing role. You'll be equally comfortable whiteboarding an architecture with a CTO or Enterprise Architect, digging into data models and pipelines alongside Engineering, and explaining how the proposed solution creates measurable business value.
Reporting to the Director of Solutions Architecture, you'll partner closely with Account Executives throughout the sales cycle, with primary ownership of technical evaluations and pilots. You'll also work with Customer Success through onboarding and initial enablement, help architect expansion opportunities within existing accounts, and bring structured feedback from the field directly to Product and Engineering.
Responsibilities
- Lead Technical Discovery & Solution Design - Translate customer data environments, GenAI initiatives, security requirements, integrations, and deployment constraints into clear, deployable target architectures.
- Own Technical Evaluations - Lead architecture, security, and deployment conversations throughout the sales cycle, serving as the technical authority for senior customer stakeholders.
- Design & Guide Proof-of-Value Pilots - Define success criteria and lead pilots using real customer data, building alongside Engineering to demonstrate measurable value and validate the path to production.
- Architect for Production & Expansion - Define reference architectures that guide customers from pilot through production deployment, scale, and additional use cases within existing accounts.
- Build & Influence - Develop reusable reference architectures, ontology templates, and solution best practices while bringing structured field insights back to the CTO, Product, and Engineering teams.
Requirements
- Solution Architecture Expertise - 7-12+ years in solutions architecture, technical pre-sales, enterprise architecture, data/AI engineering, or similar customer-facing technical roles, with a track record of designing complex enterprise solutions.
- Deep Data & AI Expertise - Strong command of data modeling, data platforms, ETL/pipelines, LLMs, RAG, and agent-based systems; experience with knowledge graphs, ontologies, or semantic technologies is strongly preferred.
- Enterprise Technical Authority - Deep understanding of enterprise architecture, security, integrations, deployment strategy, and cloud environments across AWS, Azure, and/or GCP.
- Senior Stakeholder & Commercial Credibility - Comfortable leading technical conversations with Enterprise Architects, Data Leaders, CTOs, and AI Leaders, translating complex technology into business value and helping drive technical wins, conversions, and expansion.
- Hands-On & Collaborative - Proficient in modern AI development tools such as Claude Code or Cursor to build and validate solutions yourself, moving fluidly between executive-level architecture discussions and hands-on work with Engineering.
- Startup-Tested - Ex-technical founder or experience at a startup or other fast-paced, high-growth company is a strong plus; comfortable with ambiguity and moving fast.
- Builder Mentality - Scrappy, resourceful, and biased toward action; you'd rather prototype a solution than just describe one.
We Offer
- Build the Future of Enterprise AI – Help define how AI-native companies will operate over the next decade.
- Industry Leader – We've spent the last eight years becoming a leader in enterprise AI knowledge. Now we're building the next chapter.
- Backed by World-Class Investors – Join a company supported by leading investors and trusted by many of the world's largest enterprises.
- Accelerate Your Career – You'll wear more hats, own more projects, and gain more exposure in a year than most people get in several. There are very few places where you'll learn this much, this quickly.
Compensation & Benefits
- Compensation – Competitive base salary + very meaningful equity.
- Flexible PTO
- Medical, Dental & Vision – Comprehensive health coverage.
© Shelf. This job description was sourced from the employer's public career page. TheJob is not the employer — we index the posting and route candidates to the source. All content rights and hiring decisions belong to the employer.
Shelf is an American product company building an award-winning GenAI knowledge platform, used by industry leaders such as Amazon, Nespresso, Glovo, and others.We help global enterprises prepare, organize, and enrich their unstructured data so their GenAI can give accurate, trustworthy answers from day one.Our stack combines advanced LLMs, search, retrieval, and intelligent document processing to turn messy enterprise data into production-ready GenAI answers.At Shelf, you’ll work with the latest AI/ML tools (OpenAI, Claude, Databricks, Azure OpenAI, etc.), design and launch new product features, and help solve core challenges: unstructured data, knowledge graphs, RAG pipelines, real-time search, and AI trust & explainability.See your solutions go live for millions of users from Day 1. Join a team where innovation, product ownership, and an AI-first culture come together.
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