AI Platform Engineer

Instructure
Budapest, Hungary
Hybrid

Who this role is best for

Best suited to backend engineers with LLM integration expertise working in the education technology domain, who are comfortable with hybrid work arrangements and collaborative team dynamics.

Best fit for

  • Candidates with experience in building REST/GraphQL APIs and LLM-powered services in edtech
    — “build and maintain core LLM-powered services and APIs to power the next generation of online learning tools”
  • Individuals who have shaped AI best practices in cloud infrastructure and developer tooling
    — “Establish best practices for AI and LLM use at Instructure, considering things like auditability, cost, and performance”
  • Engineers who thrive in collaborative environments and can translate complex systems into intuitive tooling
    — “Collaborate with feature teams to understand their needs and solve them with platform capabilities”

Things to consider

  • Onsite work is required on specific days, which may not align with remote-preference candidates
    — “This role requires working onsite on Tuesday and Wednesday, with Thursday strongly encouraged”
  • Candidates must be prepared for identity verification and background checks
    — “All employees must pass a background check as part of the hiring process”

How to stand out

  • Emphasize your experience in abstracting complex systems into intuitive APIs for product teams
    — “Design and implement APIs and domain services that abstract the complexity of using an LLM”
  • Showcase your background in building scalable cloud infrastructure with AWS
    — “Build scalable AWS infrastructure for LLM interactions”
  • Highlight past contributions to developer tooling and API documentation
    — “Background in developer tooling and API documentation is preferred”
Pace · SteadyCollaboration · HighAutonomy · MediumDecision Impact · Team

Derived from job-description analysis by Serendipath's career intelligence engine.

What success looks like

  • designing and implementing APIs for LLMs
  • building scalable AWS infrastructure
  • creating developer tooling
Typical background
prior software engineering experiencestrong experience with backend services and APIs

Skills & requirements

Required

API DesignDistributed SystemsLLM IntegrationAWS InfrastructurePrompt ManagementContext HandlingAuditingResponse ProcessingDeveloper ToolingAPI Documentation

Preferred

Node.jsTypeScript

Stack & domain

API DesignDistributed System DevelopmentBackend ServicesREST ApisGraphql ApisLLM IntegrationCloud InfrastructureAWSNode.jsTypeScriptDeveloper ToolingAPI Documentation

About the role

Original posting from Instructure via Ashby

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:

At Instructure, we empower teachers and learners to grow and succeed by creating intuitive products that simplify learning, facilitate meaningful relationships, and inspire innovation.

We are looking for AI Platform Engineers to build and maintain core LLM-powered services and APIs to power the next generation of online learning tools. On this team, you’ll design and implement services and infrastructure that will allow our feature teams to rapidly develop and deploy LLM-powered features that improve the teaching and learning experience of tens of millions of people around the world while maintaining our high standards for performance, security, and reliability.

What You’ll Do

  • Design and implement APIs and domain services that abstract the complexity of using an LLM and enable rapid feature development from our product teams;
  • Build scalable AWS infrastructure for LLM interactions, including prompt management, context handling, auditing, and response processing;
  • Create developer tooling and documentation that makes integration with your services intuitive and easy;
  • Establish best practices for AI and LLM use at Instructure, considering things like auditability, cost, and performance;
  • Collaborate with feature teams to understand their needs and solve them with platform capabilities;
  • Design, develop, and maintain scalable and performant APIs;
  • Write clean, maintainable, and well-documented code;
  • Participate in code reviews and provide and receive constructive feedback

What You’ll Need

  • Prior software engineering experience with API design and distributed system development;
  • Strong experience building backend services and REST or GraphQL APIs;
  • Knowledge of API design best practices around security, performance monitoring, rate limiting, and more;
  • Understanding of LLM integration and usage patterns;
  • Strong collaboration and written and verbal communication skills;
  • Past experience with cloud infrastructure, preferably on AWS;
  • Experience with Node.js or a desire to learn;
  • Experience with TypeScript or a desire to learn;
  • Background in developer tooling and API documentation is preferred.
  • 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.

Why Join Us?

  • At Instructure, you’ll be at the forefront of bringing AI into education, building the platform that powers AI-driven features across Canvas and other products. In this role, you’ll design and develop scalable, secure, and high-performance APIs and platform services that enable rapid creation of LLM-based educational tools, used by engineers across the organization.
  • You’ll collaborate closely with feature teams, establish best practices for AI use, and create developer tools that make integrating these services intuitive and seamless. Your work will directly impact millions of learners, helping teachers and students benefit from smarter, faster, and more innovative educational technology.
  • We invest in our employees’ growth and success through thoughtful mentorship, hack weeks, internal conferences, and a culture that values ownership, experimentation, and innovation. If you’re excited by building foundational AI infrastructure that empowers others and drives real-world impact, this is the role for you.

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.

Source: Instructure careers (Ashby)

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