Full-Time

Product Manager

Posted on 9/10/2026

Dust

Dust

51-200 employees

Enterprise AI agent platform

Compensation Overview

€80k - €120k/yr

Île-de-France, France

Remote

Office-first culture in Paris; occasional work from home is permitted at the employee's discretion.

Category
Product (1)
Required Skills
LLM
Product Management
Data Analysis

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Requirements
  • 5–8+ years of product experience, including experience at an early-stage company where processes had to be built from scratch.
  • Strong product judgment and the ability to distinguish excellent technology products from good ones.
  • Excellent information synthesis skills, including distilling customer feedback, sales calls, and Slack threads into clearly framed problems.
  • Technical proficiency sufficient to earn engineers' respect and understand systems and tradeoffs, without necessarily coding.
  • Fluent use of artificial intelligence tools and enthusiasm for applying them to product management operations.
  • Ability to communicate clearly and concisely.
  • Ability to operate effectively with distributed authority and influence through sound judgment rather than formal authority.
Responsibilities
  • Create and run the process connecting product signal to problem shaping and prioritization.
  • Translate company priorities into an intelligible, trackable set of product, marketing, and operations initiatives.
  • Enrich prioritized projects with distilled business context, user context, and market perspective.
  • Qualify and synthesize feedback from go-to-market teams, users, and product into a small set of well-framed problems worth solving.
  • Work with engineers and designers to translate validated problems into initiatives with clear objectives, key performance indicators, and scope.
  • Own reporting on whether shipped work produced the intended outcomes and feed the results into future decisions.
  • Connect Marketing, Communications, go-to-market, and Product to reduce coordination friction across functions.
  • Own the goals, objectives, key performance indicators, orchestration, and reporting for cross-functional initiatives.
  • Own artifacts in the Dust platform, including agents, skills, and data, to continuously improve the work for the role and team.

Dust provides a horizontal, open-source platform to design, deploy, and manage custom AI agents that connect to a company's internal data and tools. It works by acting as an operating-system for AI: connects LLMs from OpenAI, Anthropic, Google, and Mistral to company data and tools (Slack, Notion, Google Drive, GitHub) through a no/low-code GUI, prompt-chain builder, building blocks, and a scripting language. The platform targets non-technical users to automate workflows across departments, enabling tasks, insights, and better decision-making, while emphasizing security with SOC 2 Type II and GDPR and maintaining model-agnosticity. Dust aims to be an enterprise AI operating system that broadens AI adoption within organizations, offering a B2B SaaS product with a horizontal strategy and a Series A from Sequoia.

Company Size

51-200

Company Stage

Series B

Total Funding

$62M

Headquarters

Paris, France

Founded

2023

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Simplify Jobs

Simplify's Take

What believers are saying

  • Dust raised $40M in May 2026 from Sequoia, Abstract, Snowflake Ventures, and Datadog.
  • It claims 3,000-plus organizations, 300,000 agents deployed, 70% weekly usage, and zero churn.
  • New 2026 releases—Skills, Sidekick, Triggers, and ten MCP integrations—expand automation depth quickly.

What critics are saying

  • OpenAI, Anthropic, Microsoft, and Google can bundle comparable agent controls into suites by 2027.
  • Dust’s value proposition depends on model providers it does not control, risking margin compression.
  • If governance or trigger failures hit customers, enterprise trust collapses and procurement freezes.

What makes Dust unique

  • Dust’s 2026 platform centers on multiplayer AI, shared context, and governed agent workflows.
  • Its model-agnostic stack now supports GPT-5.6, GPT6 Astra, Claude, Gemini, and Mistral.
  • Anthropic’s 2025 Europe partnership and 2026 Paris event validate Dust’s ecosystem position.

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Benefits

Health Insurance

Company Equity

Relocation Assistance

Company Social Events

Growth & Insights and Company News

Headcount

6 month growth

-1%

1 year growth

1%

2 year growth

0%
Noah Business Intelligence
Jul 18th, 2026
Dust raises $40M Series B to build collaborative AI agents that work across teams

Dust, an enterprise AI platform, has raised $40m in a Series B round led by Abstract and Sequoia, with backing from Snowflake and Datadog. Chief executive Gabriel Hubert says the company is moving beyond individual AI tools towards shared agents integrated into company workflows. These "digital teammates" can be assigned tasks, linked into chains, and pass work between stages. Hubert argues this approach institutionalises operational knowledge rather than just improving individual productivity. The model addresses growing governance concerns. Data from Smarsh shows 55% of large EU enterprises use AI, yet only a quarter believe their governance frameworks are fully prepared. Dust ties agents to controlled workspaces where administrators manage data access and permissions. Hubert expects that by 2027, companies will focus less on whether to use agents and more on managing and governing them effectively.

Contentsquare
Jun 24th, 2026
Contentsquare partners with Dust to power AI agents with customer experience & digital performance data.

Contentsquare partners with Dust to power AI agents with customer experience & digital performance data. CSQ Platform Paris - June 24, 2026 - Contentsquare, a global leader in customer experience intelligence, today announced a new integration with Dust, the leading enterprise platform for building and deploying secure AI agents. The integration gives teams direct access to Contentsquare's customer experience intelligence within Dust. Instead of switching between dashboards, building reports, and interpreting analytics, users can ask questions in natural language and get immediate answers grounded in real customer behavior. Bringing customer Intelligence Into everyday workflows. Understanding customer behavior often requires navigating multiple tools, pulling data, and translating findings into actions. Valuable insights exist, but accessing them can be slow and highly dependent on specialist teams. The Contentsquare MCP connector for Dust removes that friction. Teams can query live behavioral data directly from Dust AI agents, turning customer experience insights into something that's available wherever work happens. Whether investigating a drop in conversion, identifying friction in a checkout flow, or understanding the impact of a recent release, teams can get answers in minutes - along with the context needed to take action. By combining Contentsquare's behavioral data with Dust's agent platform, organizations can automate analysis, generate structured briefs, trigger workflows, and surface customer insights directly in the tools teams already use. From behavioral data to automated decision support. The Contentsquare MCP connector equips Dust agents with real-time access to critical behavioral datasets, enabling several cross-functional use cases: * Funnel & journey analysis briefs: Agents automatically extract step completion times, drop off rates and end to end funnel conversion rates to help you see where you're losing visitors so you can prioritise fixes. * Quantified revenue impact: Dust leverages Contentsquare's Impact Analysis to rank friction points and errors by their exact financial downside, allowing teams to ruthlessly prioritize sprint cycles. * Automated behavioral digests: Teams can set up autonomous, scheduled workflows inside Dust to deliver weekly or daily plain-English performance summaries to stakeholders via email - completely touch-free. * Error spike triage & routing: The connector accesses real-time JavaScript and API error rates and session impact metrics. When anomalies occur, Dust agents can generate immediate technical briefs or route triage notes directly into connected engineering ecosystems like Slack or Jira. * Multi-source business reasoning: Fuse experience data with complementary data sources so Dust can provide a unified view of business insights across the entire tech stack. Turn customer experience data into instant AI-powered insights. Connect Contentsquare with Dust to help your teams query real customer behavior, automate analysis, and act faster, without jumping between dashboards. Availability. The Contentsquare MCP connector for Dust is available starting today for joint customers. To learn more about setting up the integration or to read the Use Case Playbook, visit contentsquare.com or dust.tt. Gabrielle Moreau Global Communications and Public Affairs Manager at Contentsquare Gabrielle Moreau is Contentsquare's Global Communications and Public Affairs Manager. She leads media relations, executive communications, and partner PR across EMEA and the US, and oversees the company's public affairs strategy from Paris, France. Prior to Contentsquare, she held corporate communications roles at Bouygues and BNP Paribas. * Press & Media Contentsquare Brings CX Intelligence Into Claude to Improve Experiences and Drive Growth Contentsquare, a global leader in customer experience intelligence, today announced it is among the first experience analytics solutions to be listed in Anthropic's Claude Connectors Directory. * Press & Media - 4 min read Contentsquare acquires Hotjar to help all businesses build better digital experiences The two leaders join forces to serve the global market end-to-end - from entrepreneurs & SMBs/growth companies to Enterprises Wednesday, September 1, 2021 - Contentsquare, the global leader in digital experience analytics, today announces it is joini...

Axios
May 18th, 2026
Dust raises $40M Series B led by Abstract and Sequoia for AI agent platform

Dust, a human-agent collaboration platform, raised a $40M Series B led by Abstract and Sequoia. CEO Gabriel Hubert announced the round exclusively via Axios.

Tech.eu
May 18th, 2026
Dust raises $40M Series B to build the "multiplayer" operating system for enterprise AI.

Dust raises $40M Series B to build the "multiplayer" operating system for enterprise AI. Used by more than 3,000 organisations, Dust claims over 300,000 AI agents have already been deployed across its platform with 70 per cent weekly active usage and zero churn in 2025. Agentic AI company Dust today announced a $40 million Series B led by Abstract and Sequoia, with participation from Snowflake and Datadog. With this round, Dust has raised over $60 million in total funding. Most companies have adopted AI, but they haven't become meaningfully more intelligent as organisations. One person prompts an assistant, gets an answer, and the context disappears into a private chat window. The result is real productivity at the individual level, with very little compounding across teams. Dust is on a mission to transform how work gets done. It is the Operating System for AI Agents. It enables businesses to deploy, orchestrate, and govern fleets of specialised AI agents that work alongside the team, safely connecting the company's knowledge and tools. "This is a century-defining transformation, and we're only in year three," said Gabriel Hubert, Co-Founder and CEO of Dust. "What will transform the way we work isn't the next best model or assistant. It's going to be a completely new type of system that gives humans and agents shared, governed access to the same information and capabilities so that they become true collaborators, working with the same context, notifications, artifacts, and goals to compound organisational impact. This is what we call multiplayer AI, and this is what we're building at Dust." Dust is the multiplayer AI system for human-agent collaboration. It's a platform where business teams build, deploy, and manage AI agents that work together across an organisation, connected to company knowledge, integrated with the tools teams already use, and governed with enterprise-grade controls. The product is built around a shared collaboration surface where teams and agents work in the same workspace with shared projects, context, conversations, to-dos, notifications, and a cloud-based compute environment for processing files and generating documents. An intelligence layer connects more than 100 data sources and integrates with tools teams already rely on, enabling agents to work with company context and take action. Built-in memory and reinforcement loops help teams achieve more impact with AI over time by understanding their preferences and proactively recommending agent improvements. Enterprise governance provides granular permissions, cost and usage monitoring, a full audit trail, and agent analytics. Dust is SOC 2 Type II certified, GDPR compliant with EU and US data residency, and does not train models on customer data, as contractually guaranteed by major providers. Dust is used by more than 3,000 organisations, many of them household names. Over 300,000 agents have been deployed across the platform, with 70 per cent weekly active usage across customers and zero churn in 2025. The company was founded by Gabriel Hubert and Stanislas Polu, who have been building together since meeting at Stanford in 2007. They previously co-founded TOTEMS, a data analytics company acquired by Stripe in 2014, and spent five years at Stripe scaling products and teams. Polu later joined OpenAI as a research engineer on Greg Brockman's team, co-authoring papers on AI reasoning with Ilya Sutskever. Hubert became Chief Product Officer at Alan. In September 2022, Polu left OpenAI with a conviction that became Dust's founding thesis: the models were already powerful enough to be economically transformative, but were under-deployed because the product layer was missing. "We're in the early innings of a massive shift in how organisations use AI," said Konstantine Buhler, Partner at Sequoia. "Most enterprise AI today is single-player: one person, one prompt, no compounding. Dust is building the multiplayer system, where agents and humans share context and work together across the entire company. Zero churn and 70 per cent weekly active usage tell you this isn't experimental anymore. This is how enterprises will actually operate." "Most AI platforms are stuck in single-player mode: one person, one chatbot, one task," said Ramtin Naimi, General Partner at Abstract. "Dust is multiplayer. AI Operators inside companies like Datadog and 1Password don't just use Dust; they build agents that collaborate across teams, learn from every interaction, and rewire how the entire company works. That's a new operating model and category. That's why we participated in this round." Dust plans to use this round to push three frontiers at once: agents that learn and improve automatically as they're used, collaboration primitives that make humans and agents equal co-contributors with bidirectional access to shared projects, tools, and context, and infrastructure that makes governance and orchestration predictable at enterprise scale. Lead image: Dust founders Stanislas Polu and Gabriel Hubert. Follow the developments in the technology world. What would you like us to deliver to you?

SiliconANGLE Media
May 18th, 2026
Dust raises $40M to shift enterprises from isolated AI chatbots to collaborative agents

Dust, an enterprise AI startup, has raised $40 million in a Series B round led by Abstract and Sequoia Capital, with participation from Snowflake and Datadog. The funding brings total capital raised to over $60 million. The Paris-based company addresses the problem of isolated AI chatbots operating in silos across organisations. Its platform enables "multiplayer AI", where agents and humans collaborate on shared workspaces, accessing conversations, tasks and documents together. The system connects to over 100 enterprise platforms including Slack, Notion and Salesforce. Dust has attracted more than 3,000 organisations globally, which have deployed over 300,000 agents. The company reported zero customer churn in 2025 and a 70% weekly active user rate. The funding will accelerate development of specialised AI agents that learn and improve collaboration capabilities.