Staff Engineer, Customer Insights
Together AI · San Francisco, CA · Engineering
About this role
Together AI is hiring a principal-level Principal Engineer in the software engineering function based in San Francisco, CA. The posting calls out experience with Python, TypeScript, Java, Kubernetes. Compensation is listed at $200,000–$270,000 per year.
- Role
- Principal Engineer
- Function
- software engineering
- Level
- principal
- Track
- Tech leadership
- Employment
- Full-time
- Location
- San Francisco, CA
- Department
- Engineering
More roles at Together AI
Job description
from Together AI careersStaff Engineer, Customer Insights
About the role
Together AI is seeking an experienced Staff Engineer to help found, build, and scale Customer Insights, the team responsible for the customer-facing visibility layer of Together’s Cloud. This role will shape how customers understand their activity, investigate what happened, respond when something needs attention, and govern their AI workloads with confidence.
In the near term, you will turn today’s fragmented visibility patterns into coherent product and platform foundations: historical analytics, activity history, audit logs, event timelines, notifications, and investigation workflows. You will partner closely with Together’s cloud product engineering teams and data platform team to make high-quality customer visibility a built-in capability across Together Cloud rather than a bespoke effort for each surface. Longer term, you will shape how these foundations evolve beyond dashboards and static views into AI-first investigation and insight workflows: systems that can summarize activity, explain anomalies, correlate events across surfaces, recommend actions, and provide trustworthy context to both human operators and autonomous agents.
This is a deeply hands-on role for an engineer who enjoys critical-path product and platform work. You will design the event, query, delivery, and governance systems behind customer insights while also building the user-facing workflows that help enterprise customers answer: what happened, who acted, when it happened, what matters now, and whether they need to act.