Senior Software Engineer, Data
Summary
This role involves building and maintaining the data platform and backend services that power AI features for an educational platform. You will design data models, manage ingestion pipelines, and ensure system reliability in a production environment using Python, SQL, and AWS.
Our AI team is where a lot of that gets built: applying advanced AI to real problems in learning, and turning research into product capabilities that educators and students use every day.
We're building the data platform behind our AI features: the models, pipelines, and services that hold the data those features depend on. This role owns it in production.
You’ll design the data models, build the services and pipelines that keep them current, and ensure they remain reliable as usage and complexity grow. This is backend and data engineering for systems where getting the structure of the data right is the core challenge.
You'll work alongside data scientists and applied AI engineers who build on what you own, and with our infrastructure team on deployment and operations.
Why Join Us
Join us and help shape the future of education by turning cutting-edge AI into reliable product capabilities.
At Instructure, we're on a mission to help educators and students learn together, anytime, anywhere, and however works best. You'll join our research-driven team tackling education's biggest challenges with cutting-edge technology.
We value diversity, creativity, and passion, and invest in our teams through mentorship, hack weeks, internal conferences, and a culture where innovation thrives. Here, you'll have the chance to build the next generation of LMS features that make a real impact on students and teachers, and do it in a collaborative, supportive environment that encourages experimentation and growth.
What You'll Need
- Six or more years of experience building and operating production backend, data, or distributed systems
- Strong production Python and SQL, including experience building APIs, designing schemas, optimizing queries, and working with large or complex datasets
- Deep experience with relational data systems and strong judgment about when graph or other specialized databases are the right choice
- Experience building reliable ingestion and update pipelines, including incremental processing, data-quality checks, schema changes, and safe backfills
- Experience designing production services with clear API contracts, versioning, error handling, and performance considerations
- Hands-on experience deploying and operating services in AWS using containers, CI/CD, monitoring, and production debugging tools
- Strong engineering practices around testing, code review, observability, documentation, and maintaining systems that other teams depend on
It Would Be a Bonus If You Had
- Deep experience operating a graph database in production, including traversal performance and query tuning at scale
- Experience with versioned, bitemporal, or event-sourced data systems
- Experience with vector search or semantic retrieval components (pgvector, OpenSearch, Pinecone, or similar)
- Experience with multi-tenant data design and per-tenant isolation
Onsite Collaboration Requirement: This role requires working onsite on Tuesday and Wednesday, with Thursday strongly encouraged as part of our company’s in-person collaboration model.