Job description

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? 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.) Our feature store enables organizations to manage, serve, and monitor features at scale—delivering the foundation that banks, financial services firms, and enterprise customers depend on to power mission-critical machine learning workloads. We’re looking for a Senior Principal Software Engineer to own and drive our feature store product. This is a unique opportunity to shape the technical direction of a product that serves some of the world’s most demanding customers, while building a world-class engineering team. THE ROLE As Senior Principal 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. - Lead V2 Implementation: Architect 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 shape the technical roadmap. Translate customer requirements and market trends into actionable engineering priorities. - Engage with Strategic Customers: Serve as a trusted technical advisor to banks, financial institutions, and enterprise customers. Lead technical discussions, understand their ML infrastructure challenges, and ensure our platform meets their needs. - Build & Mentor the Team: Recruit, coach, and develop engineers. Foster a culture of technical excellence, ownership, and continuous improvement. - Stay Hands-On: Actively participate in design reviews, code reviews, and critical implementation work. Lead by example in technical decision-making. - 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 - 8+ years of experience in backend/infrastructure engineering, with demonstrated expertise in building large-scale distributed systems - 3+ years in a technical leadership role—leading teams, driving architecture decisions, and mentoring engineers - 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 Redis is committed to building a diverse and inclusive workplace. We are an equal opportunity employer and welcome candidates of all backgrounds. #LI-BL1 #Remote 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 orientation, age, marital status, disability, gender identity, gender expression, Veteran status, or any other classification protected by federal, state, or local law. We strive to create a workplace where every voice is heard, and every idea is respected. Redis is committed to working with and providing access and reasonable accommodation to applicants with mental and/or physical disabilities. If you think you may require accommodations for any part of the recruitment process, please send a request to recruiting@redis.com. All requests for accommodations are treated discreetly and confidentially, as practical and permitted by law. Any offer of employment at Redis is contingent upon the successful completion of a background check, consistent with applicable laws. Redis reserves the right to retain data longer than stated in the privacy policy redis.com in order to evaluate candidates.

Requirements

Must-haves

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.
Lead V2 Implementation: Architect 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 shape the technical roadmap. Translate customer requirements and market trends into actionable engineering priorities.
Build & Mentor the Team: Recruit, coach, and develop engineers. Foster a culture of technical excellence, ownership, and continuous improvement.
Stay Hands-On: Actively participate in design reviews, code reviews, and critical implementation work. Lead by example in technical decision-making.
Drive Adoption of Modern Practices: Champion the use of AI-assisted development tools, observability best practices, and infrastructure automation to accelerate delivery.
8+ years of experience in backend/infrastructure engineering, with demonstrated expertise in building large-scale distributed systems
3+ years in a technical leadership role—leading teams, driving architecture decisions, and mentoring engineers
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-haves

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

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

machine learningmlaipythongorustawsgcpazure

Platform: ashby
Effort: quick

Benefits

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Vision