Together AI

Together AI

Software Engineer, Customer Insights

San Francisco · Full-time

Sponsorship not specified$150k-$200kDetected 1 day ago
TypeScriptPythonJavaGoC++Distributed SystemsFull-Stack DevelopmentAlgorithmsCode ReviewData EngineeringResearch

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odds of building a lasting career here

37Unrated
Cap-exempt (no lottery)0
Sponsors this role0
Entry-level history0
PERM / green-card track0
Lottery odds (Level IV)94
Fits your clock70

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About the role

  • Together.ai is looking for a Software Engineer to join the Customer Insights team - a great role for a full-stack or backend engineer who wants to grow into event-driven systems, analytics, and the customer visibility space.
  • You'll get guidance as you take on unfamiliar problem spaces, with plenty of room to grow toward more autonomy over time.
  • We pair, review each other's code, and learn in the open - it's a strong environment to level up in.

Responsibilities

  • Build and ship features for Together's Customer Insights platform, including customer-visible events, activity history, audit logs, timelines, notifications, and historical analytics and dashboards views.
  • Own well-defined pieces of work end-to-end, from implementation through testing and rollout
  • Write and maintain critical-path backend and product code used by multiple teams and customer-facing surfaces.
  • Surface blockers early and collaborate with the team to work through them
  • Help maintain the freshness, completeness, and correctness checks that keep customer-facing visibility systems trustworthy
  • Developing data modeling instincts - comfort working with schemas, queries, and relational and/or non-relational data

Requirements

  • 2-5 years of experience building and operating large-scale distributed systems, product platforms, or customer-facing backend systems in production environments.
  • Genuine enthusiasm to learn event-driven systems, analytics pipelines, and the customer visibility space - deep prior experience isn't required, and we'll support you in getting there

Nice to have

  • Interest in, or some exposure to, stream processing, data pipelines, notification systems, or analytical systems (this is a great team to learn them on)
  • About Together AI
  • Together AI is a research-driven artificial intelligence company.
  • We have contributed to leading open-source research, models, and datasets to advance the frontier of AI, and our team has been behind technological advancement such as FlashAttention, Hyena, FlexGen, and RedPajama.
  • Individual compensation will be determined by experience, skills, and job-related knowledge.

Compensation

  • We offer competitive compensation, startup equity, health insurance and other competitive benefits.
  • The US base salary range for this full-time position is: $150k - 200k + equity + benefits.
  • Our salary ranges are determined by location, level and role.
  • Individual compensation will be determined by experience, skills, and job-related knowledge.

Benefits

  • $150k - 200k + equity + benefits.

Company info

  • the historical analytics, activity history, audit logs, event timelines, notifications, and investigation workflows that help customers understand their activity and govern their AI workloads with confidence.
  • 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.

Equal opportunity

  • Together AI is an Equal Opportunity Employer and is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and more.

Visa & Work Authorization

  • t opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and more

This listing is sourced directly from Together AI's careers page and normalized into a canonical job model.