Senior Principal Software Engineer, Feature Store
Leads technical vision, architecture, and V2 development of Redis Feature Store for large-scale ML infrastructure. Requires 8+ years backend experience, expertise in Python/Go/Rust, cloud platforms, and data tools; mentors team and engages enterprise customers.
About the job
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
Skills
Python, Go, Rust, AWS, GCP, Azure, Kafka, Flink, Redis, Spark, Feast, Tecton, Hopsworks
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