AI Software Engineer

Requirements:

·       Experience in software integration, API development, or automation engineering.

·       Experience working with SIS, LMS, and education technology platforms.

·       Strong proficiency in API development, automation workflows, and event-driven architectures.

·       Knowledge of cloud-native integration tools in AWS, Google Cloud Platform, or Azure.

·       Excellent problem-solving skills and an automation-first mindset.

·       Strong ability to collaborate with AI, cloud, and data engineering teams to create scalable AI-driven solutions.

·       Familiarity with LLMs and AI-powered automation is a plus.

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Responsibilities:

• Design and implement integrations between AI models and school systems (SIS, LMS, student data platforms, and assessment tools).

·       Work with common SIS & LMS platforms such as PowerSchool, Infinite Campus, Blackbaud, Canvas, Moodle, Google Classroom, and Microsoft Teams for Education.

·       Develop middleware, APIs, and automation scripts to enable AI-enhanced workflows for grading, student engagement analysis, and predictive insights.

·       Build, deploy, and manage RESTful APIs, GraphQL APIs, and Webhooks to enable seamless communication between AI and school infrastructure.

·       Automate data extraction, transformation, and synchronization between systems using ETL pipelines and API-driven workflows.

·       Develop integrations with LLM-based AI assistants, chatbots, and recommendation engines to enhance learning experiences.

·       Leverage low-code and no-code automation tools where applicable for rapid deployment of solutions.

·       Ensure real-time data flow between AI tools and student management systems using Pub/Sub, Kafka, or event-driven architectures.

·       Implement secure authentication and authorization protocols (OAuth 2.0, SAML, JWT) to protect student and faculty data.

·       Ensure compliance with FERPA and other education data privacy regulations.

·       Work with identity and access management (IAM) solutions to control AI system permissions.

·       Work closely with AI teams, data engineers, and DevOps to deploy integrations in AWS and Google Cloud Platform.

·       Develop serverless functions (AWS Lambda, Google Cloud Functions, Azure Functions) for lightweight, scalable automation.

·       Implement event-driven architectures using Step Functions, Pub/Sub, and Webhooks.

·       Collaborate with educators and administrators to define integration requirements and automation opportunities.

Technical Stack & Tools

Integration & API Development:

·       RESTful APIs, GraphQL, gRPC

·       OAuth 2.0, JWT, SAML, OpenID Connect

·       Postman, Swagger (OpenAPI), API Gateway

Cloud & Infrastructure:

·       AWS (Lambda, Step Functions, API Gateway, EventBridge, S3, DynamoDB)

·       Google Cloud Platform (Cloud Functions, Pub/Sub, Firestore, BigQuery)

·       Azure (Azure Functions, Event Grid, Cosmos DB)

Automation & Data Pipelines:

·       Python, Node.js, FastAPI, Flask, Express.js

·       ETL tools (Talend, dbt)

·       Messaging & Streaming: Kafka, RabbitMQ, Redis Pub/Sub

Security & Compliance:

·       IAM & Role-Based Access Control (RBAC)

·       Data encryption, secure API access

·       Compliance with FERPA