Senior Software Engineer, Feature Store

Redis
United StatesPosted 15 April 2026

Job Description

Senior Software Engineer, Feature Store Who we are We're Redis. We built the product that runs the fast apps our world runs on. (If you checked the weather, used your credit card, or looked at your flight status online today, you’re welcome.) At Redis, you’ll work with the fastest, simplest technology in the business—whether you’re building it, telling its story, or selling it to our 10,000+ worldwide customers. We’re creating a faster world with simpler experiences. You in? THE ROLE As Senior Software Engineer for our Feature Store product, you will be the driving force behind our platform. You’ll own the technical vision, lead execution, and serve as the primary technical voice with our most strategic customers—including major banks and enterprise organizations with demanding requirements around performance, reliability, and compliance. This role blends deep technical leadership with customer-facing responsibilities. You’ll spend time architecting systems, guiding the roadmap, setting engineering standards, and engaging directly with customers to understand their needs and translate them into product capabilities. WHAT YOU’LL DO • Own Technical Excellence: Define and drive the architecture, design patterns, and engineering standards for the feature store platform. Set a high bar for code quality, system reliability, and performance. • V2 Implementation: Assist and execute the next generation of our feature store—building for scale, low-latency serving, and enterprise-grade reliability. • Guide Product Roadmap: Partner with Product and leadership to help shape the technical roadmap. Translate customer requirements and market trends into actionable engineering priorities. • Drive Adoption of Modern Practices: Champion the use of AI-assisted development tools, observability best practices, and infrastructure automation to accelerate delivery. WHAT YOU’LL NEED • 5+ years of experience in backend/infrastructure engineering, with demonstrated expertise in building large-scale distributed systems • Deep experience with ML infrastructure, data platforms, or feature engineering systems at scale • Expertise in Python, Go, and Rust • Strong knowledge of cloud platforms (AWS, GCP, Azure) and modern data infrastructure (Kafka, Flink, Redis, Spark, or similar) • Experience working with enterprise customers, particularly in regulated industries like financial services • Excellent communication skills—able to translate complex technical concepts for both engineering teams and business stakeholders NICE TO HAVE • Direct experience building or operating feature stores (Feast, Tecton, Hopsworks, or custom implementations) • Experience with real-time feature serving at sub-millisecond latencies • Background in financial services, banking technology, or compliance-heavy environments • Contributions to open-source ML infrastructure projects • Hands-on experience as a data scientist or ML practitioner—training and deploying models in production WHY JOIN US • High-Impact Role: Own a critical product line and directly influence how the world’s leading organizations build ML systems • Enterprise Customers: Work with banks, financial institutions, and Fortune 500 companies solving real, complex problems • Technical Depth: Tackle challenges in distributed systems, low-latency serving, and ML infrastructure at scale • Competitive Compensation: Salary, equity, and comprehensive benefits • Flexible Work: Remote-friendly culture with flexibility to do your best work As a global company, we value a culture of curiosity, diversity of thought, and innovation from our employees, customers, and partners. Redis is committed to a diverse and inclusive work environment where all employees’ differences are celebrated and supported, and everyone feels safe to bring their authentic selves to work. Redis is dedicated to equal employment opportunities regardless of race, color, ancestry, religion, sex, national orientation, sexual orientat ... (truncated, view full listing at source)
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