Principal AI Sales Specialist
Cohesity · Utica-Rome Area · 1 mo ago
Business Development$354k–$443k/yrFull-time
We need to output HTML fragment with sections: About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. Only include sections that have real specific content. Must not repeat job title. Must not include Job ID etc. Must preserve all substantive info. Remove boilerplate: cookie/navigation/legal/EEO/equal-opportunity/scam-warning, duplicated lines, application instructions. Also remove EEO statements, data privacy notice, etc. Keep pay range. Benefits: mention comprehensive benefits framework etc. Schedule: In-Office Expectations: 2-3 days a week in office for those within commute. That's schedule info. So include Schedule section.
We need to parse the posting.
Let's extract sections:
About the role: description of Cohesity, GAIA, why now, founding GTM role, etc. That's substantive.
Responsibilities: "HOW YOU’LL SPEND YOUR TIME HERE:" bullet list (though not bullet but sentences). We'll convert to
- . Requirements: maybe "WE’D LOVE TO TALK TO YOU IF YOU HAVE MANY OF THE FOLLOWING:" list of qualifications/experience. That's requirements. Qualifications: maybe "Bachelor's degree required." plus "Professional English language proficiency". Also "Demonstrated ability to leverage AI tools". Could be part of qualifications. Skills: maybe "Working fluency in the AI landscape", "Experience selling both product/infrastructure and consulting-advisory engagements", "Proven ability to build and deliver executive-grade decks", "Comfort operating in a co-sell / specialist model", "Disciplined CRM and forecasting habits". Could be skills. Benefits: "Additionally, full-time employees are eligible to participate in our comprehensive benefits framework, including health and wellness benefits, vacation, paid holidays and refresh days, 401(k) retirement plan, life and disability insurance coverages, and other benefits the Company may offer from time to time." Pay: "Pay Range : $354,400.00-$443,000.00" plus mention of bonus, commission, equity. Schedule: "In-Office Expectations Cohesity employees who are within a reasonable commute (e.g. within a forty-five (45) minute average travel time) work out of our core offices 2-3 days a week of their choosing. We strongly prefer candidates who are currently located in or near the designated job location. Candidates outside the area should apply only if they are committed to relocating prior to their start date and have the legal right to work in the job location." We need to remove application instructions like "If you are an individual with a disability..." etc. Also remove EEO statements, Data Privacy Notice, etc. Also remove duplicated lines. We must not invent or summarize away detail. Must preserve all substantive info. So we need to keep all the details from the posting, but we can rephrase? The instruction: "Preserve ALL substantive information; do NOT invent or summarize away detail." Means we should keep the content, not omit details. However we can format into HTML but must keep the info. We can keep sentences as is, maybe break into list items. We must not add filler like "commensurate with experience". Not present. We must not create sections with placeholder text. Thus we will produce sections: About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. We need to ensure each section has content. Let's extract content precisely. About the role: The first paragraphs up to "Why now:"? Actually "About the role" could be the introductory description: "Cohesity is a leader in AI-powered data security and management...". Then description of GAIA, why now, founding GTM role. We'll combine into a few paragraphs. Responsibilities: The list after "HOW YOU’LL SPEND YOUR TIME HERE:" includes many sentences. We'll turn each sentence into a
- . Requirements: The list after "WE’D LOVE TO TALK TO YOU IF YOU HAVE MANY OF THE FOLLOWING:" includes bullet points numbered 1-... We'll turn each into
- .
Qualifications: Could be "Bachelor's degree required." and "Professional English language proficiency for customer and internal communication." Also "Demonstrated ability to leverage AI tools to enhance productivity, streamline workflows, and support decision making." Might be considered qualifications.
Skills: Could be "Working fluency in the AI landscape: platforms, deployment models, use cases, value drivers, and where the risk actually sits." etc. Also "Experience selling both product/infrastructure and consulting-advisory engagements to enterprise, data-driven, or high-growth technology customers." etc. Also "Proven ability to build and deliver executive-grade decks and proposals that hold up in front of a buying committee." etc. Also "Comfort operating in a co-sell / specialist model — you drive the AI motion, field account teams own the primary relationship, and you make that partnership work." etc. Also "Disciplined CRM and forecasting habits." etc.
But we need to avoid duplication. Some items appear both in requirements and skills. We'll keep them where they appear.
We must not repeat job title.
We'll output HTML fragment.
Let's craft.
First, About the role:
Cohesity is a leader in AI-powered data security and management. Aided by an extensive ecosystem of partners, Cohesity makes it easy to secure, protect, manage, and get value from data — across the data center, edge, and cloud. Cohesity helps organizations defend against cybersecurity threats with comprehensive data security and management capabilities, including immutable backup snapshots, AI-based threat detection, monitoring for malicious behavior, and rapid recovery at scale. We’ve been named a Leader by multiple analyst firms and have been globally recognized for Innovation, Product Strength, and Simplicity in Design. Join us on our mission to shape the future of our industry. GAIA is Cohesity’s enterprise AI platform for unlocking the value of unstructured data across the Cohesity Data Cloud. It helps customers securely search, understand, summarize, and reason across current and historical enterprise information, while preserving permissions, provenance, and governance. GAIA also provides a foundation for agentic AI by making trusted enterprise context available to AI applications, copilots, and agents - helping customers move from simply protecting data to using it as a strategic source of intelligence and action. Why now: This role is a founding GTM role in Cohesity's new AI Business Unit. GAIA is where the market is heading - enterprises secured their data with us; now they want to activate it for AI. You'll build the sales playbook on top of 13,000 existing customers and co-sell muscle from NVIDIA and the hyperscalers, carrying a brand-new number in a market that's just opening. Ground floor, executive air cover, and a partner ecosystem already generating pipeline.
That seems good. Responsibilities: after "HOW YOU’LL SPEND YOUR TIME HERE:" we have list: - Own GAIA revenue number across product/infrastructure and consulting-advisory bookings for your territory — you generate it, you carry it, you close it. - Be the AI subject-matter resource in every deal you touch — data architecture, use cases, deployment models, and the business case behind them, credible enough to hold the room with a CAIO, CDO, or VP of AI. - Build pipeline, Partner with marketing, SDRs, and field sales, but don't wait on them — daily and weekly outbound across multiple channels is part of the job, not a fallback. - Identify, qualify, develop, and close AI opportunities by working existing field relationships and building new ones with your own network. - Build and deliver executive-quality pitch decks, proposals, and business cases that translate the technology into a value story specific to the account — not a template with a logo swapped in. - Blend product/infrastructure opportunities with consulting and advisory engagements into multi-phase account plans — the first deal should set up the next one. - Work the AI partner ecosystem for your region — NVIDIA, the hyperscalers, infrastructure OEMs, and emerging AI vendors — for joint pipeline, co-sell motion, and deal registration. - Run disciplined pipeline hygiene: accurate CRM, honest stage progression, forecasts people can plan against. - Show up in cadence calls and pipeline reviews with something useful — market intel, competitive read, what worked and what didn't — not just a status update. We'll put each as - . Requirements: after "WE’D LOVE TO TALK TO YOU IF YOU HAVE MANY OF THE FOLLOWING:" list: 1. 10-12 years of quota-carrying technology sales experience, including time in a specialist selling role, with 2-3 years specifically selling AI products to VP of AI, CAIO, CDO, or equivalent buyers. 2. Infrastructure selling experience — you know what it takes to get a platform decision made, not just a point-tool purchase. 3. A demonstrated track record generating your own pipeline in complex, multi-stakeholder enterprise accounts — hunter, not order-taker. 4. Working fluency in the AI landscape: platforms, deployment models, use cases, value drivers, and where the risk actually sits. 5. This is a business-value and consultative-selling role, not a hands-on technical practitioner seat. 6. Experience selling both product/infrastructure and consulting-advisory engagements to enterprise, data-driven, or high-growth technology customers. 7. Proven ability to build and deliver executive-grade decks and proposals that hold up in front of a buying committee. 8. Comfort operating in a co-sell / specialist model — you drive the AI motion, field account teams own the primary relationship, and you make that partnership work. 9. Disciplined CRM and forecasting habits. 10. If it's not in the system, it doesn't count. 11. Bachelor's degree required. 12. Demonstrated ability to leverage AI tools to enhance productivity, streamline workflows, and support decision making. 13. Professional English language proficiency for customer and internal communication. We could separate qualifications vs requirements. But the instruction: Use sections like Requirements, Qualifications, Skills. We need to decide what goes where. We could treat the numbered list as Requirements (experience). Then Qualifications: Bachelor's degree required, Professional English language proficiency, Demonstrated ability to leverage AI tools. Skills: Working fluency in AI landscape, Experience selling both product/infrastructure and consulting-advisory engagements, Proven ability to build executive-grade decks, Comfort operating in co-sell model, Disciplined CRM and forecasting habits. But note some items overlap: "Working fluency in the AI landscape" appears also in requirements list (item 4). We'll keep it under Skills maybe, but we must not lose it. If we put it only under Skills, we still preserve it. The requirements list also includes that item; we could keep it under Requirements as well, but that would duplicate. Better to keep each piece only once. We need to decide categorization. Let's map: Requirements (experience): - 10-12 years of quota-carrying technology sales experience, including time in a specialist selling role, with 2-3 years specifically selling AI products to VP of AI, CAIO, CDO, or equivalent buyers. - Infrastructure selling experience — you know what it takes to get a platform decision made, not just a point-tool purchase. - A demonstrated track record generating your own pipeline in complex, multi-stakeholder enterprise accounts — hunter, not order-taker. - Experience selling both product/infrastructure and consulting-advisory engagements to enterprise, data-driven, or high-growth technology customers. - Comfort operating in a co-sell / specialist model — you drive the AI motion, field account teams own the primary relationship, and you make that partnership work. - Disciplined CRM and forecasting habits. - If it's not in the system, it doesn't count. Qualifications: - Bachelor's degree required. - Professional English language proficiency for customer and internal communication. - Demonstrated ability to leverage AI tools to enhance productivity, streamline workflows, and support decision making. Skills: - Working fluency in the AI landscape: platforms, deployment models, use cases, value drivers, and where the