Intern — Integration Developer

Mirantis

About The Position

Mirantis is seeking a technically curious intern to join as an Integration Developer. This role involves working on real projects from day one, focusing on connecting enterprise systems, building API integrations, and gaining hands-on experience with AI-powered automation alongside experienced engineers.

Requirements

Technical Python and/or JavaScript/Node.js fundamentals.
Working knowledge of REST APIs, JSON, OAuth2.
Git and GitHub — branching, commits, pull requests, merge conflict resolution.
Basic SQL skills.
Comfortable using AI coding assistants (Copilot, Cursor, Claude).
Basic understanding of LLMs: context windows, tool calling, prompt design.
Awareness of responsible AI use: hallucination risks, data privacy, output validation.
Understanding of common API security risks.
Basic knowledge of authentication and authorization patterns: OAuth2, API keys, JWT.
Awareness of data handling responsibilities: PII, access control, and audit logging.
Jira for task tracking, sprint planning, and issue management.
GitHub for version control, pull requests, and collaborative code review.
Comfortable working in an Agile team environment.
Strong analytical and problem-solving mindset.
Clear written and verbal communication in English.
Detail-oriented, collaborative, and self-directed.
Comfortable with ambiguity and fast-moving environments.

Nice To Haves

Familiarity with cloud platforms or Docker is a plus.
Basic understanding of LLMs: context windows, tool calling, prompt design.
Awareness of responsible AI use: hallucination risks, data privacy, output validation.

Responsibilities

Build and maintain integrations between internal systems (CRM, ITSM, ERP) using REST and GraphQL APIs.
Develop data pipelines to move, transform, and sync data across platforms.
Work with iPaaS tools such as Make, Zapier, Boomi, or MuleSoft.
Debug integration failures and data issues across distributed systems.
Write clean, documented code in Python and/or JavaScript.
Connect LLM APIs (Claude, OpenAI) into internal workflows and business applications.
Build MCP connectors to enable AI agents to interact with enterprise systems.
Help design and test multi-agent workflows using LangChain, AutoGen, or CrewAI.
Prototype AI-native patterns: document parsing, ticket classification, semantic search, and RAG pipelines.
Monitor AI pipelines for accuracy and unexpected behavior; iterate based on results.
Write tests to validate integration and pipeline behavior.
Participate in code reviews — both giving and receiving structured feedback via GitHub pull requests.
Apply basic security practices: secret management, input validation, OAuth2 scopes, and least-privilege API access.
Identify and flag common integration security risks such as exposed credentials, insecure endpoints, and excessive data exposure.
Document API contracts, data mappings, and configurations.
Maintain runbooks and contribute to the internal knowledge base.