Senior Infrastructure Engineer, AI/ML Systems

📋 Job Overview

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. This is a hands-on delivery role. You'll build the deployment path that takes models and AI services from prototype to production, and you'll keep them running once they're there. You'll be one of two engineers who own infrastructure for this team, which means wide scope, real ownership, and direct influence over how we build. You'll work closely with data scientists, applied AI engineers, and product partners to turn advanced AI ideas into reliable product capabilities used at scale.

🏢 About Instructure

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.

🎯 The Role

This is a hands-on delivery role. You'll build the deployment path that takes models and AI services from prototype to production, and you'll keep them running once they're there. You'll be one of two engineers who own infrastructure for this team, which means wide scope, real ownership, and direct influence over how we build. You'll work closely with data scientists, applied AI engineers, and product partners to turn advanced AI ideas into reliable product capabilities used at scale.

✅ Key Responsibilities

• Build and operate deployment pipelines for AI services, covering CI/CD, infrastructure-as-code, environment promotion, and rollback
• Deploy and operate model serving, batch scoring, and orchestration pipelines across development, staging, and production
• Partner with data scientists and applied AI engineers to take prototypes into production, including system design for net-new services
• Own production reliability for AI services: monitoring, alerting, debugging, performance, and cost
• Spot repeated patterns and turn them into reusable templates, so the team can ship its second and third variant of something without rebuilding it

📌 Required Qualifications

• Six or more years in infrastructure, DevOps, platform, or ML engineering, with ownership of systems running in production
• Deep hands-on experience across a wide range of AWS services, including compute, networking, storage, deployment, and monitoring
• Infrastructure-as-code experience (Terraform, CDK, or CloudFormation)
• Experience with containers and modern deployment patterns (Docker required, Kubernetes or ECS/EKS a plus), applied to CI/CD pipelines you've designed and operated for production services
• Experience with orchestration and workflow tooling (Airflow, Dagster, Argo, Step Functions, or similar)
• Comfort working through ambiguity and collaborating directly with data scientists and researchers

⭐ Desirable Experience

• Experience with ML platform components and data pipeline orchestration at scale
• Experience running LLM-based or retrieval-based systems in production
• Experience operating specialized data stores, including graph databases
• Experience building internal tooling, templates, or reference implementations that other engineers adopted

🎁 Benefits

• 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

🛂 Visa & Eligibility

• 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.