Staff Engineer, Customer Insights

Together AI•San Francisco, CA

About The Position

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.

Requirements

8+ years of experience building and operating large-scale distributed systems, product platforms, or customer-facing backend systems in production environments.
Proven experience designing platforms or product systems used by multiple engineering teams or enterprise customers.
Strong backend engineering skills in one or more of TypeScript, Go, Python, Java, C++, or similar production languages.
Deep experience with event-driven systems, audit trails, activity feeds, analytics platforms, observability systems, notification systems, or investigation workflows.
Strong data modeling and systems design judgment, including schemas, retention, indexing, query performance, access control, and correctness tradeoffs.
Demonstrated ability to turn ambiguous customer and operational needs into clear technical architecture, incremental delivery plans, and durable product foundations.
Experience partnering across product, infrastructure, data, security, and customer-facing teams to land cross-cutting architecture without relying on formal authority.
Comfort writing critical production code while also setting technical direction, mentoring senior engineers, and raising engineering standards.
Bachelor's or Master's degree in Computer Science, Computer Engineering, a related technical field, or equivalent practical experience.

Nice To Haves

Experience building enterprise SaaS audit logs, governance tooling, compliance evidence systems, data lineage, or incident investigation products.
Experience with high-volume event pipelines, streaming systems, OLAP or time-series storage, search systems, or large-scale analytical query engines.
Experience building notification, alert routing, escalation, or workflow automation systems.
Experience designing customer-facing analytics, reporting, dashboards, or operational intelligence products.
Experience with multi-tenant cloud platforms, identity-aware access patterns, sensitive data handling, and retention controls.
Experience with AI infrastructure, developer platforms, observability, or systems that support mission-critical enterprise workloads.
Experience running production workloads on Kubernetes or cloud infrastructure and using Infrastructure as Code and modern CI/CD workflows.
Experience building product surfaces in addition to backend platforms, especially where UX quality and technical correctness both matter.

Responsibilities

Design and drive the architecture for Together's Customer Insights platform, including customer-visible events, activity history, audit logs, timelines, notifications, and historical analytics and dashboards views.
Build and operate the shared event and historical analytics visibility layer that helps product teams define important customer-facing events once and surface them consistently across analytics, logs, timelines, notifications, and governance views.
Write and maintain critical-path backend and product code used by multiple teams and customer-facing surfaces.
Partner with Data Platform and Observability engineering teams to leverage Together’s core data stack and capabilities to build out Customers Insights data collection and processing systems.
Create customer workflows that connect summaries, timelines, evidence, actors, related objects, and next steps so users can investigate operational questions without relying on support or ad hoc analysis.
Establish standards and review patterns for which events, evidence trails, notification hooks, and governance signals must exist before new product capabilities launch.
Define reliability, freshness, completeness, and correctness measures for customer-facing visibility systems, then build the checks and operating loops needed to maintain trust at scale.
Mentor engineers, influence architectural direction across teams, and help define the hiring bar as the Customer Insights area grows.