Senior/Group Product Manager, AI Ecosystem & Semantic Layer
Sigma Computing· enterprise· Data analytics· Jun 10, 2026 · 5mo agoPosted 139 days ago
San Francisco, CA
In office
Full-time
Senior
$200K–$250K
5+ years exp
Before you apply
Ghost Signal:
Open since June 10, 2026 — 139 days, and still accepting applications.
Job 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.
Come join us!
Benefits For Our Full-Time Employees:
Equity
Generous health benefits
Flexible time off policy. Take the time off you need!
Paid bonding time for all new parents
Traditional and Roth 401k
Commuter and FSA benefits
Lunch Program
Dog friendly office
Sigma is an equal opportunity employer. We are committed to building a smart and strong team regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender, gender identity or expression, veteran, or any other protected status. We look forward to learning how your experience can enable all of us to grow.
Note: We have an in-office work environment in all our offices in SF, NYC, London and Sydney. All roles have a 25% travel expectation unless explicitly stated otherwise.
Our Privacy Practices
When you submit a job application on this site, Sigma processes your personal data for the purposes of evaluating your candidacy for employment at Sigma and as otherwise needed throughout the recruitment and hiring process. Please review Sigma’s Candidate Privacy Notice for more details. Please note that your personal data may be transferred to a country other than the one in which it was provided (including to the USA, the UK, and Canada, Australia).
Sigma’s use of AI
This hiring process utilizes artificial intelligence tools to assist in candidate screening and assessment. Our AI tools are designed to complement, not replace, human decision-making.
Application prep
Use the role’s language and application details while tailoring your materials.
Keywords to mirror
aisqlpython
- Platform
- greenhouse
- Effort
- quick
Benefits
Benefits detected in the listing.
401k