Senior Software Engineer, Streaming

Attentive • US

JavaTypeScriptPython Remote

Attentive® is the AI marketing platform for 1:1 personalization redefining the way brands and people connect. We’re the only marketing platform that combines powerful technology with human expertise to build authentic customer relationships. By unifying SMS, RCS, email, and push notifications, our AI-powered personalization engine delivers bespoke experiences that drive performance, revenue, and loyalty through real-time behavioral insights.

Recognized as the #1 provider in SMS Marketing by G2, Attentive partners with more than 8,000 customers across 70+ industries. Leading global brands like Crate and Barrel, Urban Outfitters, and Carter’s work with us to enable billions of interactions that power tens of billions in revenue for our customers.

With a distributed global workforce and employee hubs in New York City, San Francisco, London, and Sydney, Attentive’s team has been consistently recognized for its performance and culture. We’re proud to be included in Deloitte’s Fast 500 (four years running!), LinkedIn’s Top Startups, Forbes’ Cloud 100 (five years running!), and Inc.’s Best Workplaces.

About the Role

We’re looking for a highly driven Software Engineer with a strong grasp of distributed systems and streaming technologies. In this role, you’ll help lead our move to managed streaming platforms, expand self-service tools for developers, and ensure our event streaming infrastructure is robust, efficient, and reliable. Your work will enable faster innovation and directly support new customer-facing features at Attentive.

What You'll Accomplish

Architect and evolve Attentive’s next-generation event streaming platform: Design high-throughput, low-latency solutions that power mission-critical messaging, personalization, and data integration use cases across Attentive’s ecosystem

Drive the transition to managed services: Lead the migration from legacy infrastructure to managed event streaming platforms (e.g., Managed Kafka, Confluent), reducing operational overhead and enabling greater scale

Enhance self-service for product engineering and data teams: Build and refine self-serve tools for event observability, debugging, load testing, and system configuration, empowering teams to experiment and ship quickly

Simplify and modernize streaming architecture: Remove unnecessary abstraction layers, enable direct access for power users, and ensure the platform is flexible for both “paved path” and advanced use cases

Solve complex distributed systems challenges: Improve event delivery reliability, cost efficiency, and system integration for real-time and batch workloads

Champion best practices and technology selection: Stay ahead of industry advancements in event streaming, advocating for tools and approaches that balance innovation with long-term reliability

Collaborate across engineering: Partner with product, data, and infrastructure teams to launch new customer-facing features, integrations, and scalable solutions built on streaming infrastructure

Your Expertise

Proven experience architecting and supporting high-throughput, distributed systems at scale—especially those involving event streaming or messaging platforms

Deep understanding of the internals of distributed streaming frameworks such as Kafka, Flink, Pulsar, and/or Spark

Proficient in Java (Spring Boot) and familiar with modern development practices, including object-oriented design, data structures, and algorithms

Able to debug issues across the stack—from message serialization and event schemas to network and JVM tuning—and communicate tradeoffs clearly

Familiar with resource scheduling, data locality, and how infrastructure choices impact cost and system behavior

Experience with observability and developer tooling for streaming (e.g., tracing, metrics, replay).Infrastructure-as-code expertise (Terraform, Helm), comfortable with Kubernetes (EKS) and cloud-native environments

Track record of modernizing platforms: sunsetting legacy systems, moving to managed services, or implementing self-service capabilities

Excited by new technologies, but pragmatic about introducing them—focused on solving real business problems

What We Use

Event streaming: Apache Kafka, Pulsar, Flink

Cloud infrastructure: AWS EKS (Kubernetes), Terraform, Helm, Datadog, Istio, CloudFlare

Backend: Java, Spring Boot, Gradle, DynamoDB, Postgres, Redis, and other AWS-native services

Frontend/tools: (As relevant for observability dashboards) React, TypeScript, GraphQL, Storybook, Vite

Automation/data: Python, open-source frameworks for testing and observability, with integrations for ML and analytics use cases

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