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General Manager, Agent Management

AI Summary
Dataiku is seeking a senior general manager to own and scale its newly launched Agent Management business from initial customer wins toward $100M in revenue. The role sets cross-functional strategy across product, engineering, marketing, sales, services, and partnerships while co-owning revenue performance with the sales organization. Reporting to the CEO, the leader will establish market positioning, packaging, pricing, go-to-market motions, and product priorities for enterprise AI-agent governance. Success requires experience building a business line or company, credibility with technical executive buyers, and strong financial and operational judgment. The position is remote within the United States and includes worldwide customer, partner, and office travel.
Remote from
USA
Salary
Undisclosed
Employment
Full Time
Experience
Open level
Published
Apply before
8 Dec 2026
Listing views
48
Application actions
4
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Opportunity details

About this role.

Dataiku is the Platform for AI Success, the enterprise orchestration layer for building, deploying, and governing AI. In a single environment, teams design and operate analytics, machine learning, and AI agents with the transparency, collaboration, and control enterprises require. Sitting above data platforms, cloud infrastructure, and AI services, Dataiku connects the full enterprise AI stack – empowering organizations to run AI across multi-vendor environments with centralized governance.

The world’s leading companies rely on Dataiku to operationalize AI and run it as a true business performance engine delivering measurable value. For more, visit the Dataiku blog, LinkedIn, X, and YouTube.

Enterprises run AI agents across many platforms and vendors, and they need one independent place to see, manage, and control them. Agent Management gives them that. It is a product Dataiku just launched, in a category that is just forming. Dataiku is used by 25% of the Fortune 500, which gives Agent Management a route to market no startup in the category has. And because Dataiku is independent of any cloud, model, or application vendor, it can manage agents across all of them.

How you’ll make an impact

You will be the single-threaded owner of Agent Management: from first customers to $100M, with the mandate to get product, engineering, marketing, sales, services, and partners working to one plan. The category is new, and you will write the playbook for it.

You will report to the CEO and co-founder and work with the CTO and co-founder. You will have one direct report, the Head of Growth, Agent Management. Owners in Product, Engineering, Marketing, Sales, and Services stay in their teams, are accountable to you for this business, and meet in one recurring forum you run to review pipeline, launches, and blockers and leave with decisions.

You own the strategy for Agent Management (product priorities, packaging, pricing model, positioning), and you co-own the revenue number with the sales team.

In your first year, you will:

  • Win the first paying customers, learn which problem makes them buy and who owns that problem, and turn it into a motion the field can repeat.
  • Set the route to market across the installed base, new logos, partners, and OEM, with the CRO, the CMO, and Partnerships.
  • Make the first win land fast: every new customer sees all their agents in one place within weeks of signing, and that win becomes their reason to expand.
  • Agree release priorities with Product and Engineering for what your first customers need to expand.
  • Position the category with Marketing and Analyst Relations.

What you’ll need to be successful

  • You know how to build a plan to scale a business from zero to $100M, and you have carried the revenue number for one: a product line, a business unit, a new market, or a company you founded.
  • You love pitching to technical buyers: platform, security, and AI governance teams.
  • You get teams working toward one business goal, and you have results to show for it.
  • You build the financial model yourself and can explain the product to a CIO.
  • You decide fast on incomplete information, argue in the open (including with the CEO), and change your position when the data calls for it.
  • You work AI-native. You run agents in your own work, so you know the problems our buyers face when their teams run agents on many platforms.
  • You are US-based (or willing to relocate), and ready to travel to customers, partners, and Dataiku offices worldwide.

What are you waiting for!

At Dataiku, you’ll be part of a journey to shape the ever-evolving world of AI. We’re not just building a product; we’re crafting the future of AI. If you’re ready to make a significant impact in a company that values innovation, collaboration, and your personal growth, we can’t wait to welcome you to Dataiku! And if you’d like to learn even more about working here, you can visit our Dataiku LinkedIn page.

Our practices are rooted in the idea that everyone should be treated with dignity, decency and fairness. Dataiku also believes that a diverse identity is a source of strength and allows us to optimize across the many dimensions that are needed for our success. Therefore, we are proud to be an equal opportunity employer. All employment practices are based on business needs, without regard to race, ethnicity, gender identity or expression, sexual orientation, religion, age, neurodiversity, disability status, citizenship, veteran status or any other aspect which makes an individual unique or protected by laws and regulations in the locations where we operate. This applies to all policies and procedures related to recruitment and hiring, compensation, benefits, performance, promotion and termination and all other conditions and terms of employment. If you need assistance or an accommodation, please contact us at: reasonable-accommodations@dataiku.com


Protect yourself from fraudulent recruitment activity

Dataiku will never ask you for payment of any type during the interview or hiring process. Other than our video-conference application, Zoom, we will also never ask you to make purchases or download third-party applications during the process. If you experience something out of the ordinary or suspect fraudulent activity, please review our page on identifying and reporting fraudulent activity here.

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This job listing has been manually reviewed by the Jobicy Trust & Safety Team for compliance with our posting guidelines, including verification of the company's legitimacy, accuracy of job details, clarity of remote work policy, and absence of misleading or fraudulent content.

Role DNA

A quick view of the complexity, pace, ownership and collaboration implied by the job description.

Job Complexity

5/5
EasyHard

Pace & Pressure

5/5
RelaxedFast-paced

Autonomy Level

5/5
GuidedFull ownership

Communication Load

5/5
IndependentCollaborative
AI insightThis is a highly ambiguous, executive-level zero-to-scale mandate in an emerging category, with direct accountability for commercial traction and cross-functional execution. The leader must make rapid decisions with incomplete market data while aligning senior stakeholders and technical buyers.

Salary analysis

Estimated compensation compared with the broader US market for similar roles.

Estimated job median (per year)Market rate
$350,000
US market range (per year)$280k–$450k
AI insightThe yearly pay period is inferred from the job context; it was not explicitly stated by the employer. No employer base salary was disclosed. The annual USD compensation estimate is inferred from the US-based executive scope, revenue ownership, reporting line to the CEO, and responsibility for scaling a new enterprise AI product business; it excludes bonus, commission, and equity.

Core skills

Skills and capabilities most closely associated with this opportunity.

Sample interview questions
How would you build a repeatable go-to-market motion for a new Agent Management category?

I would begin with a focused set of design-partner customers to identify the highest-value governance and visibility problems, the economic buyer, and measurable outcomes. I would convert those findings into a narrow initial ideal customer profile, proof-of-value playbook, sales enablement assets, packaging, and success metrics before expanding across installed-base, new-logo, partner, and OEM channels.

Describe how you have owned a revenue number while influencing teams outside your reporting line.

I establish a shared operating model with explicit revenue goals, leading indicators, decision owners, and a recurring business review. I align product, sales, marketing, and services around a single plan, surface blockers transparently, and use customer and pipeline data to make trade-offs quickly without relying on hierarchical control.

What would you prioritize in the first 90 days?

I would validate priority customer use cases, map the buying committee, assess pipeline and installed-base opportunities, and define a small number of lighthouse accounts. In parallel, I would create a unified operating cadence, clarify product gaps that block expansion, and align leadership on the initial positioning, commercial model, and success metrics.

How would you explain Agent Management to a CIO or AI governance leader?

I would frame it as an independent enterprise layer that gives leaders visibility, governance, and control over AI agents running across multiple platforms and vendors. The value is reduced operational and governance risk, faster deployment of useful agents, and a consistent way to manage an increasingly fragmented AI environment.

How do you make decisions when market information is incomplete?

I separate reversible decisions from irreversible ones, define the few assumptions that matter most, and seek fast evidence from customers, usage, and commercial signals. I make the best decision available, communicate the rationale and metrics clearly, and revise the approach quickly when new data disproves an assumption.

This analysis is generated from the job description. Salary estimates, role characteristics and sample answers are guidance, not employer-provided facts.
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