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New York, New York, United States · On-site
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Lead pre-sales technical discovery and design deployable AI architectures for enterprise customers. Guide proof-of-value pilots and define reference architectures to ensure successful production rollout and account expansion.
Requires 8-12+ years of experience in solution architecture or AI engineering with deep expertise in GenAI, RAG, and data modeling. Must have a proven track record of engaging senior technical stakeholders and a bachelor's degree in a technical field.
No H-1B, OPT, or visa sponsorship will be provided or accepted.
Everyone is talking about agentic AI. One problem: nobody is handing the keys to an agent that still guesses. One hallucination in a 20-step workflow, and everything breaks.
The real bottleneck isn't the model. It's deterministic answers. Deterministic answers require an enterprise knowledge vault. We've spent the last eight years building exactly that.
Now we're building the rest of the stack.
The AI Solution Architect is Shelf's solution design authority in customer-facing engagements, translating complex enterprise data and GenAI challenges into concrete, deployable architectures. This role combines deep expertise in AI systems, enterprise architecture, and data modeling with the ability to engage senior technical stakeholders and design end-to-end solutions that prove measurable value and scale into production.
You'll engage early in the sales cycle, leading pre-sales technical conversations on architecture, security, and deployment strategy with senior prospect and customer stakeholders. Operating at a high level, you'll run technical discovery, design the target solution, and guide proof-of-value pilots that demonstrate Shelf's value on a prospect's real data, working directly alongside Engineering throughout. Beyond the initial win, you'll define the reference architecture that guides production rollout and expansion.
Reporting to the Field CTO, you'll partner with Account Executives throughout the sales cycle, with primary responsibility during technical evaluation and pilots. You'll collaborate with Customer Success through deal closing, onboarding, and initial enablement, and contribute to our land-and-expand growth strategy by architecting solutions that grow within existing accounts. Your insights from the field will feed directly into product direction through structured feedback to our CTO and Product leadership.
The ideal candidate brings 8-12+ years combining deep technical depth in data and AI platforms with customer-facing solution design. You're equally comfortable whiteboarding a target architecture with a CTO and getting into the detail of a pilot alongside Engineering. You communicate credibly at a senior level while maintaining the technical depth to go deep when it counts. Experience with knowledge graphs, ontologies, or semantic technologies is strongly preferred, though exceptional data modeling and architecture expertise can substitute.
Lead pre-sales technical conversations on architecture, security, and deployment strategy with senior prospect and customer stakeholders.
Lead solution design and technical discovery, translating customer data architectures, GenAI initiatives, and integration requirements into concrete target architectures.
Design and guide proof-of-value pilots that prove measurable value on customer data, working directly alongside Engineering.
Define reference architectures and solution designs that guide production rollout and scale within accounts.
Present solutions to Enterprise Architects, Data Leaders, AI/ML Engineers, and senior technical decision-makers, translating technical capabilities into business value.
Support Account Executives throughout sales cycles with primary ownership during technical evaluation and pilot phases.
Collaborate with Customer Success through deal closing, onboarding, and initial enablement.
Support existing customer expansion opportunities as part of our land-and-expand strategy.
Build reusable ontology templates, reference architectures, and solution best practices in collaboration with the Field CTO and Engineering.
Provide structured field feedback to CTO and Product leadership to influence roadmap and strategic direction.
Solution Architecture Expertise – Designs end-to-end technical solutions and reference architectures; translates ambiguous enterprise requirements into clear, deployable designs.
Enterprise Technical Authority – Strong, current command of GenAI, LLMs, RAG, and agent-based systems, combined with enterprise architecture, security, and deployment strategy; credible with senior technical stakeholders.
Data & Ontology Modeling – Strong data modeling, data platforms, and ETL/pipeline expertise; knowledge graphs and ontologies experience strongly preferred.
Senior Stakeholder Engagement – Comfortable leading high-level conversations with senior prospect and customer stakeholders such as Enterprise Architects, Data Leaders, CTOs, and AI Leaders; translates technical concepts into business value.
Customer-Facing Excellence – Exceptional communication and presentation skills; comfortable whiteboarding architectures and guiding technical evaluations.
Collaborative Delivery – Works directly alongside Engineering during pilots to prove value on real customer data.
Sales-Oriented Mindset – Understands enterprise sales cycles and is motivated by technical wins, conversions, and expanding existing accounts.
Continuous Learner – Stays current with AI/GenAI trends, data technologies, and modern engineering practices.
8-12+ years in solutions architecture, technical pre-sales, enterprise architecture, or data/AI engineering in customer-facing roles.
Strong solution design and enterprise architecture experience, including security and deployment considerations.
Strong expertise in data modeling, data platforms, and ETL/data pipelines.
Experience with knowledge graphs, ontologies, or semantic technologies strongly preferred.
Strong, current command of AI/GenAI technologies (LLMs, RAG, agent-based systems).
Deep understanding of enterprise data platforms and cloud architectures (AWS, Azure, GCP).
Technical enough to be hands-on when needed; familiarity with scripting (Python) and modern AI coding tools (Claude Code, Cursor, etc.) a plus.
Proven track record engaging senior technical stakeholders in customer-facing roles with demonstrated sales impact.
Exceptional presentation and communication skills with technical and executive audiences.
Bachelor's degree in Computer Science, Engineering, Data Science, or related field.
Experience in B2B SaaS, AI/ML, or data quality solutions preferred.
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 – Competitive base salary + very meaningful equity.
Medical, Dental & Vision – Comprehensive health coverage.
Where AI agents drive business transformation.
Shelf is an agentic operating system that enables organizations to design, optimize, and orchestrate AI agents that transform customer experience and business operations at enterprise scale.
Offices: 276 5th Ave, New York, NY 10001, US · 447 Sutter St, San Francisco, California 94108, US
Based on 6297 listings with disclosed salaries, most sales jobs in New York pay between $65k–$195k per year. Individual offers vary with seniority, company size, and specialization.
There are currently 14,353 open sales positions in New York listed on Clera. New openings are added daily as companies post roles.
Companies currently hiring include Macy's, Lowe's Companies, Inc., AutoZone, Advance Auto Parts, JPMorganChase, among others. Browse the listings above to see every active employer.
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