Senior/Group Product Manager, AI Ecosystem & Semantic Layer

We Love AI Jobs · San Francisco, California, United States

$200K to $250K a year as published by the employer

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Summary

Define strategy for an AI ecosystem and semantic layer roadmap for external integrations and developer tools.

About this role

Senior/Group Product Manager, AI Ecosystem & Semantic Layer

Sigma

San Francisco, CAFull-time$200,000 – $250,000 / year

AI tools:ClaudeChatGPT

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This product role sets strategy for Sigma’s external AI ecosystem, including MCP access, a developer CLI, marketplace presence, and integrations with workplace tools. It also owns the semantic-layer roadmap that gives AI agents and connected experiences governed, reliable data to use.

Skills and expertise

MCPCLIAPIsSlackMicrosoft TeamsGleansemantic layersdimensional modeling

Key responsibilities

How this job compares

Compared with 43 open manager product jobs on October 10, 2026.

Pay : This job pays $200K to $250K a year. The 15 open manager product jobs that publish US pay start at $168K on average, so this job starts about 19% higher.

Similar open jobs : We Love AI Jobs lists 43 open manager product jobs at 24 companies.

Remote work : This job is on site. 10 of the 43 manager product jobs (23%) are remote.

AI in this role : Medium. The role uses AI tools and works with AI systems as a regular part of the job. The role regularly shapes AI-facing product surfaces, including agent access, AI marketplaces, and data foundations for AI answers. Its focus is product strategy and delivery rather than hands-on model building.

Full description

AI only answers correctly when it can trust the data underneath it. This role owns two connected parts of how Sigma shows up in that world: where Sigma's experience lives outside its own product (MCP, a CLI, the Claude and ChatGPT marketplaces, integrations like Slack, Teams, and Glean), and the semantic layer that makes every one of those surfaces trustworthy.

The first mandate is Sigma's AI ecosystem: defining Sigma's approach to MCP, giving external agents structured, governed access to Sigma's data model; owning the CLI, giving developers a fast way to work with Sigma outside the UI; and building Sigma's presence in the Claude and ChatGPT marketplaces, plus integrations for Slack, Teams, Glean, and similar surfaces, so people can reach Sigma's data wherever they already work. This is some of the most visible, fastest-growing surface area in the product.

The second mandate is the semantic layer underneath it all. Every agent, chat answer, and integration is only as reliable as the data model behind it — get a metric definition wrong here, and every surface built on top inherits the mistake. This includes setting the roadmap for how semantic views connect across data platforms and how the model evolves as new AI capabilities emerge.

What you'll do

• Define Sigma's approach to MCP, giving external agents and tools structured, governed access to Sigma's data model.

• Own the CLI roadmap, giving developers a fast, scriptable way to work with Sigma outside the UI.

• Build Sigma's presence in the Claude and ChatGPT marketplaces, along with integrations for Slack, Teams, Glean, and similar surfaces, so people can reach Sigma's data wherever they're already working.

• Set the roadmap for Sigma's data modeling strategy, including how semantic views connect across data platforms and how the semantic layer evolves as new AI capabilities emerge.

• Partner with engineering and design to ship integration and semantic modeling capabilities that hold up at enterprise scale.

What we're looking for

• 5+ years of product management experience in B2B SaaS, data platforms, analytics, or developer-facing products

• Familiarity with MCP, APIs, or other machine-to-machine interfaces, and how agents consume structured data

• Experience building or launching integrations with platforms like Slack, Microsoft Teams, or enterprise search tools such as Glean

• Comfortable defining a CLI or other developer-facing product from the ground up

• Strong understanding of data modeling concepts (semantic layers, metrics layers, dimensional modeling) and how they connect across a modern data stack

• Some background in BI or analytics is a plus. You should be able to explain why a metric defined once in the semantic layer beats the same metric redefined five different ways across five different tools

Additional Job Details

The base salary range for this position is $200k – $250k annually, plus competitive equity and benefits packages.

Compensation may vary outside of this range depending on a number of factors, including a candidate's qualifications, skills, competencies, and experience. Base pay is one part of the Total Package provided to compensate and recognize employees for their work at Sigma Computing. This role is eligible for stock options, as well as a comprehensive benefits package.

About us:

Sigma is the AI Apps and agentic analytics platform built on the cloud data warehouse. Business and technical teams use Sigma to explore live data, build intelligent applications, and automate critical workflows all without moving data or breaking governance. Sigma supports a spreadsheet interface, SQL, Python, and native AI in a single governed workspace, giving every team the speed to act and IT the control to scale. Sigma is trusted by more than 2,000 customers, including AMD, Duolingo, Colgate-Palmolive, and JPMorgan Chase.

Sigma announced its $80M in Series E financing in May 2026. The round was led by Princeville Capital, with new strategic investors Databricks Ventures, ServiceNow Ventures, and Workday Ventures participating alongside returning investors Altimeter Capital, Avenir Growth Capital, D1 Capital Partners, K5 Global, NewView Capital, Spark Capital, Sutter Hill Ventures, and XN. This milestone follows Sigma reaching $200M in annual recurring revenue in April 2026, with more than 100% year-over-year growth and 1.1 million new active users added in the latest fiscal year.

Skills named in this posting

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