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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Software Engineer, Streaming - **Company:** ATTENTIVE PARTNERS, LLC - **Location:** New York, NY, United States - **Experience:** Expert - **Salary:** $178,400.0 - $267,600.0 - **Contract:** Permanent contract - **Skills:** Java (Programming Language), Abstraction Layers, Airflow, Amazon Web Services, Cloud Computing, System Configuration, Information Engineering, Data Integration, Serialization, Data Structures, Software Debugging, Programming Tools, Distributed Systems, Amazon DynamoDB, Gradle, Java Virtual Machine (JVM), Python (Programming Language), PostgreSQL, Load Testing, Machine Learning, Enterprise Messaging Systems, Object-Oriented Software Development, Open Source Technology, Redis, Tensorflow, Short Message Service, Software Engineering, Data Streaming, Systems Integration, TypeScript, Datadog, Pytorch, ReactJS, Istio, Apache Spark, Spring-boot, Backend, Pandas, Webpack, Kubernetes, Apache Flink, HuggingFace, Playwright, Cloudflare, Apache Kafka, Graphql, Front End Software Development, Terraform, Legacy Systems, Microservices - **Published:** November 6, 2026 - **Apply:** https://www.careerbuilder.com/job-details/senior-software-engineer-streaming-ny--1c28e4fc-07a9-4ff0-b140-82b10259c782 ## About the Role Software Engineering, Marketing, Customer Relations, Global Branding, Short Messaging Service (SMS), Mobile Marketing, Hubs, Startup, Campaigns, LinkedIn, * 5+ years 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 ## Description We're looking for a highly driven Senior Software Engineer to join our Streaming team, which powers the backbone of Attentive's messaging and personalization platform. Our event streaming systems handle over 2 million messages per second and sit at the heart of how product and data engineering teams build real-time, customer-facing experiences. In this role, you'll help shape the future of our streaming architecture, moving us to modern platforms, and unlocking new capabilities for debugging, load testing, and observability. Your work won't just keep the pipes flowing it will directly influence how quickly we can experiment, personalize, and scale across millions of devices and billions of events. This hybrid role is based in our New York office, with in-office collaboration Tuesday through Thursday each week. 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 * 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, * Our infrastructure runs primarily in Kubernetes hosted in AWS's EKS * Infrastructure tooling includes Istio, Datadog, Terraform, CloudFlare, and Helm * Our backend is Java / Spring Boot microservices, built with Gradle, coupled with things like DynamoDB, AirFlow, Postgres, and Redis, hosted via AWS * Our frontend is built with React and TypeScript, and uses best practices like GraphQL, Storybook, Radix UI, Vite, esbuild, and Playwright * Our automation is driven by custom and open source machine learning models, lots of data and built with Python, Metaflow, HuggingFace , PyTorch, TensorFlow, and Pandas