At Instructure, we believe in the power of people to grow and succeed throughout their lives. Our goal is to amplify that power by creating intuitive products that simplify learning and personal development, facilitate meaningful relationships, and inspire people to go further in their education and careers.
We do this by giving smart, creative, passionate people opportunities to create awesome. And that's where you come in:
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.
What You'll DoOwn the data models and storage architecture behind our AI systems, across relational, graph, and retrieval-oriented data
Build and operate the APIs, backend services, and pipelines that keep that data current and accessible
Design reliable ingestion and update workflows, including incremental processing, schema changes, and safe backfills
Own data correctness, query performance, and scalability as volume and complexity grow
Turn prototypes into production-ready data services, scoring workflows, and retrieval components
Diagnose production issues and improve reliability, observability, and operational efficiency
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
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.
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.
Get in on all the awesome at Instructure!
We offer competitive, meaningful benefits in every country where we operate. While they vary by location, here's a general idea of what you can expect:
Competitive compensation, plus all full-time employees participate in our ownership program - because everyone should have a stake in our success.
Flexible work culture. Our remote, hybrid and in-office collaboration spaces vary by role, team and location.
Generous time off, including local holidays and our annual “Dim the Lights” period in late December, when teams are encouraged to step back and recharge based on departmental needs.
Comprehensive wellness programs and mental health support
Learning and development resources, including professional development tools and tuition reimbursement, to support your growth
The technology and tools you need to do your best work
Motivosity employee recognition program
A culture rooted in inclusivity, support, and meaningful connection
We believe in hiring great people and treating them right. The more diverse we are, the better our ideas and outcomes.
Instructure is an Equal Opportunity Employer. We comply with applicable employment and anti-discrimination laws in every country where we operate.
All employees must pass a background check as part of the hiring process. To help protect our teams and systems, we’ve implemented identity verification measures. Candidates may be asked to verify their legal name, current physical location, and provide a valid contact number and residential address, in accordance with local data privacy laws.
Any attempt to misrepresent personal or professional information will result in disqualification.
Skills Required
- Six or more years of experience building and operating production backend, data, or distributed systems
- Strong production Python and SQL experience
- Experience building APIs, designing schemas, optimizing queries, and working with large or complex datasets
- Deep experience with relational data systems
- Experience building reliable ingestion and update pipelines, including incremental processing, data-quality checks, schema changes, and safe backfills
- Experience designing production services with 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 in testing, code review, observability, documentation, and system maintenance
- 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 such as pgvector, OpenSearch, or Pinecone
- Experience with multi-tenant data design and per-tenant isolation
Instructure Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Instructure and has not been reviewed or approved by Instructure.
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Fair & Transparent Compensation — Pay is considered market-competitive for many engineering, product, and quota-carrying roles, especially when factoring base, variable, and equity. In these tracks, total rewards are often characterized as fair-to-strong for the role and location.
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Healthcare Strength — Health coverage is described as comprehensive, including medical, dental, vision, mental-health support, and HSA/FSA options. Employer contributions are often portrayed as strong, and core medical benefits receive consistently positive marks.
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Leave & Time Off Breadth — Time off offerings include flexible or “unlimited” PTO, paid holidays, and paid sick time, paired with widespread remote/hybrid flexibility. This breadth of time off and work flexibility is often viewed as a meaningful perk that enhances overall value.
Instructure Insights
What We Do
Instructure is helping people grow from the first day of school to the last day of work. More than 30 million people use its Canvas and Bridge platforms for learning management and employee development.







