Founding Product Marketer
San Francisco, CAFull-timePosted todayStill listed today
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At a glance
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Job overview
Echelon AI is seeking its first product marketer to shape how its AI-native enterprise implementation offering is positioned and packaged. The role works across Product, Engineering, Delivery, Growth, and Sales, using customer and practitioner evidence to develop solution plays, messaging, and market-facing assets. It also establishes repeatable customer-to-market workflows and an AI-native product marketing operating system that preserves source traceability and technical integrity.
Skills & qualifications
Skills
Qualifications
Full job description
Founding Product Marketer Echelon AI · Full-time · In-person - San Francisco Reports to: Head of Product About Echelon Echelon is building an AI-native system integrator for enterprise software, starting with ServiceNow. Our agents understand a customer's environment, turn ambiguous requests into reviewable designs, build and verify the work, and document what changed. Customers can use Echelon as an AI teammate for their own practitioners or pair the technology with Echelon experts to deliver the work on their behalf.
We are a seed-stage company backed by Bain Capital Ventures. Our ambition is to replace slow, time-based enterprise implementation work with faster, more transparent, outcome-oriented delivery across ServiceNow, SAP, Salesforce, and other critical platforms. The role Echelon has more technical capability than the market can absorb in one story. The first product marketer will decide which customer jobs and solution offers should lead, make the mechanism and outcome clear to different buyers, and build the system that keeps the story coherent as the portfolio expands.
This is a founding, hands-on role. You will listen to customer and practitioner conversations, work directly with Product, Engineering, Delivery, Growth, and Sales, and personally create the first strong assets. The website, solution pages, webinars, decks, videos, field material, and event workshops are where your positioning and packaging decisions become visible and measurable.
You will also define how an AI-native product marketing function should work. Customer calls, product changes, delivery lessons, and community questions should become verified use cases, proof, and campaigns without losing their source or technical integrity. What you'll accomplish
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Establish the market and narrative truth. Identify the priority buyers, buying triggers, jobs, current alternatives, proof requirements, and unresolved claims. Audit the current story and recommend what to keep, change, remove, or validate.
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Package solution plays. Turn high-priority use cases into offers with a clear buyer, trigger, scope, outcome, technical mechanism, proof, commercial hypothesis, and next step.
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Make the story convert across the core surfaces. Own the website and solution pages, webinar narrative and slides, product and customer content, LinkedIn and founder or expert video, sales material, and technical workshops. Every asset should serve one audience, job, and measurable decision.
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Build the customer-to-market workflow. Establish a repeatable path from a customer call or product change to a verified use-case record, message decision, launch or campaign, field enablement, and performance readout.
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Make founder-led and expert-led selling repeatable. Give Sales, Growth, founders, and domain experts a consistent discovery story, demo narrative, buyer-specific message, objection response, and proof set. Use field evidence to update the system each week.
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Create an AI-native PMM operating system. Build source-linked workflows for signal capture, use-case detection, research, drafting, repurposing, claim verification, and measurement. AI should shorten the path from evidence to action without publishing generic or unverified output.
Who you are
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You have worked in product marketing or an adjacent technical GTM role at a high-growth B2B company. Strong candidates may have moved from solutions engineering, product, or technical sales into hands-on product marketing.
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You can understand a technical product deeply enough to choose what matters to a CIO, platform owner, architect, practitioner, procurement team, or partner without flattening the mechanism or overstating the result.
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You have made positioning and packaging decisions under ambiguity. You can name the buyer, trigger, alternative, promise, proof, and strongest rejected story.
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You personally produce strong work. You can turn one message spine into a website page, sales narrative, webinar, article, short video, and workshop without creating six disconnected stories.
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You use customer and market evidence to challenge internal opinion. You distinguish a repeated pattern from one loud anecdote and state what would change your view.
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You understand enterprise solution economics. You can help frame value, pricing, and proof against headcount, software, services, delay, risk, and delivered outcomes.
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You build influence without a large team or formal authority. You can tell a founder the story is unclear, help an expert become a stronger market voice, and give Sales material they will actually use.
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You use AI for leverage and retain human judgment. Your workflows preserve sources, expose uncertainty, verify claims, and improve after feedback.
How this job compares
Set against the 2,766 open Product Marketing jobs on Olive Jobs, counted October 29, 2026.
- Pay
- This postingNot listed
- California median$160–225K/yr555 salary ranges
- US median$28–44/hr41 hourly ranges
- Openings
- Olive Jobs lists 692 open Product Marketing jobs in California and 2,766 across the US. 10% of them nationwide are listed as remote or flexible.
- Experience
- Product Marketing postings that state a minimum ask for 6 years of experience at the median; the middle half ask for 4 to 8 years (2,382 postings).
- Education
- 865 of the 2,766 open Product Marketing jobs (31%) ask for a bachelor's degree or higher.
Counted across the open, public US postings on Olive Jobs on October 29, 2026. Pay medians are the middle values of the low ends and of the high ends of postings that list both ends of a range in the same cadence (a yearly salary or an hourly rate); a range's midpoint is halfway between its ends. Pay and experience figures resting on fewer than 20 postings are left out.
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