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Attentive is an AI marketing platform specializing in 1:1 personalization across SMS, RCS, email, and push notifications. The company serves over 8,000 customers across 70+ industries, including major brands like Crate and Barrel, Urban Outfitters, and Carter's, enabling billions of interactions that power tens of billions in revenue.
The Segment Optimization team builds the backbone of Attentive's audience-segmentation infrastructure, processing billions of events from over 100 million customers daily. This team enables near-real-time audience insights and AI-driven personalization through Data, Optimization, and ML Platforms.
As a Software Engineer II, you will own well-scoped features end-to-end in distributed data applications that power the segmentation platform. You'll build systems that enable clients to curate audience segments, which Attentive uses across its platform to personalize content and drive higher performance for clients and better experiences for their customers.
Key responsibilities include:
- Building and improving systems powering audience segmentation for 100+ million customers
- Owning features end-to-end across distributed data applications, from design through deployment and operation
- Partnering with engineering, product, and design teams to deliver high-quality software
- Developing deep understanding of owned services, data flow, and customer impact
- Contributing to team and engineering-wide improvements in process, infrastructure, and systems
- Leveraging AI tools to move quickly while focusing on system behavior and thoughtful design tradeoffs
Required expertise includes 2–4 years as a Software Engineer with backend services experience and desire to deepen distributed systems skills. You should have experience with Java, Python, or Go; strong understanding of object-oriented design, algorithms, and optimization; familiarity with relational and non-relational databases; and ability to write clean, correct code following best practices. You take ownership beyond assigned tasks, communicate clearly with technical and non-technical teammates, and work effectively through ambiguity.
