Description
At Instructure, we believe in the power of people to grow and succeed throughout their lives.
Our AI team applies advanced AI to real problems in learning, turning research into product capabilities used daily by educators and students.
As a Senior Infrastructure Engineer, AI/ML Systems, you'll build and operate deployment pipelines for AI services, covering CI/CD, infrastructure-as-code, environment promotion, and rollback.
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.
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
Requirements
- 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
- Infrastructure-as-code experience (Terraform, CDK, or CloudFormation)
- Experience with containers and modern deployment patterns (Docker required, Kubernetes or ECS/EKS a plus)
- Experience with orchestration and workflow tooling (Airflow, Dagster, Argo, Step Functions, or similar)
Nice to Have
- 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
Benefits
- Competitive compensation
- Flexible work culture
- Generous time off
- Comprehensive wellness programs and mental health support
- Learning and development resources
- Technology and tools needed to do your best work
- Motivosity employee recognition program