Senior Principal Software Engineer, Feature Store
Redis is hiring a Senior Principal Software Engineer, Feature Store for a remote role open to applicants in Canada. Level rates it ; you can apply on Redis.
Level's read on this job
- Level rates this software engineer role Works on AI ●●●○: the daily work is on AI products, without building the model.
- This is listed as a remote role.
- The posting mentions software architecture, distributed systems and feature store among its tools and skills.
- Level classes it as a lead role.
- Redis has 29 other open roles on Level.
AI in this role
Senior Principal Software Engineer leading the technical vision and architecture for enterprise feature store workloads.
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 in order to evaluate candidates.
How we rate this
Senior Principal Software Engineer, Feature Store at Redis rates 70 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.
Works on AI. The daily work is on AI products, without building the model.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Also common in software engineer jobs at this level
Pay
- Typical software engineer job
- $168k
This posting doesn't list pay. Use the typical software engineer figure when pay comes up. See software engineer jobs
Questions you could be asked
- Tell me about a project where software architecture was part of your work. What did you do?
- Tell me about a project where distributed systems was part of your work. What did you do?
- Tell me about a project where feature store was part of your work. What did you do?
- Tell me about a project where machine learning infrastructure was part of your work. What did you do?
- Describe a typical day in a role like this one: which parts run through AI directly?
Adapt your resume
- List these exact terms on your resume: Software Architecture, Distributed Systems, Feature Store, and Machine Learning Infrastructure. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Show where AI is part of your daily process, not a one-off project. This role expects it to be a running habit.
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