Staff Software Engineer, Streaming
AttentiveUnited States$209k – $250kPosted 23 March 2026
Tech Stack
Job Description
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!), Inc.’s Best Workplaces , and the Human Rights Campaign Foundation's Corporate Equality Index !
About the Role
Attentive’s streaming platform is the backbone of our messaging and personalization ecosystem, powering billions of events and processing over 2 million messages per second in real time. It sits at the center of how engineering teams across Attentive build responsive, customer-facing products at scale.
We’re looking for a Staff Software Engineer to help lead the evolution of this platform into its next generation. In this role, you’ll set technical direction for streaming architecture across the company, drive major modernization efforts, and build the primitives, tooling, and standards that enable product and data teams to move faster with confidence. Your impact will extend well beyond a single service or team: you’ll shape how Attentive scales real-time systems, improves reliability and observability, and unlocks new capabilities for experimentation, personalization, and growth.
This is a high-leverage role for an engineer who thrives on solving deeply technical distributed systems problems, influencing platform strategy, and raising the bar for how we build and operate streaming infrastructure across the organization.
What You’ll Accomplish
Architect and evolve Attentive’s next-generation event streaming platform; design high-throughput, low-latency, and cost-efficient solutions that power mission-critical products and use cases across Attentive’s ecosystem.
Enhance streaming developer experience: Build and refine self-serve tools for event observability, debugging, load testing, and system configuration, empowering teams to experiment independently 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 with primitives for reliable stream processing: rate limiting, deduping, delayed message delivery, etc.
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
10+ years of experience architecting and supporting high-throughput, distributed systems at scale—especially those involving event streaming or messaging platforms.
Strong expertise in the internals, tradeoffs, and operating models of distributed streaming technologies such as Kafka, Flink, Pulsar, and/or Spark.
Proven track record of leading major platform or architectural initiatives that span multiple teams, includi ... (truncated, view full listing at source)
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