At Globe, our goal is to create a wonderful world for our people, business, and nation. By uniting people of passion who believe they can make a difference, we are confident that we can achieve this goal.

Job Description

The AI Engineer Intern will assist in designing, prototyping, and integrating Artificial Intelligence solutions across internal enterprise systems and customer-facing platforms. Moving beyond theoretical ML coursework, this role focuses on the practical mechanics of modern AI engineering: working with LLM orchestration frameworks, retrieval systems (RAG), vector storage, and data preparation pipelines under the direct mentorship of senior AI engineers

Duties And Responsibilities

GenAI & Agent Pipeline Assistance: Support senior engineers in prototyping and testing retrieval-augmented generation (RAG) pipelines, semantic search modules, and basic agentic workflows using frameworks like LangChain or LlamaIndex.
Data Ingestion & Semantic Prep: Clean, transform, and index structured and unstructured datasets for embedding generation, vector database storage, and semantic layer integration.
Testing & Model Evaluation: Conduct empirical evaluations of LLM outputs—measuring context relevancy, ground-truth alignment, and mitigation of hallucinations across model revisions.
Integration & Reusable Code: Write clean, modular Python code and REST API wrappers to package AI features into reusable SDKs or microservices.
Documentation & Version Control: Maintain code hygiene using Git/GitOps best practices and author clear technical documentation for architecture, API endpoints, and setup guides.

Deliverable/s

Completion of a working, end-to-end module (e.g., a functional agent tool or optimized RAG index) presented to the CDA leadership team at the end of Month 4.

KPIs

Technical Velocity & Autonomy: Speed at which the intern transitions from requiring step-by-step guidance to independently taking on developer tickets and debugging pipelines.
Code & Engineering Quality: Consistency in Git workflows, code readability, unit testing, and adhering to enterprise engineering standards.
Execution on AI Evaluation: Ability to quantitatively measure model performance, prompt reliability, and output accuracy on assigned tasks.

Skills

Programming: Strong foundation in Python (OOP, async, data structures) and basic SQL
AI / GenAI Frameworks: Academic exposure to ML concepts, basic prompt engineering, and API usage (e.g., OpenAI, Hugging Face).
Data & Vector Prep: Experience with pandas, numpy, and parsing unstructured documents (PDFs, JSON, text)
Software Tools: Familiarity with Git, Linux command line, and REST API concepts (FastAPI/Flask).
Soft Skills & Aptitude: Rapid learning capability, structured problem-solving, curiosity, and attention to detail

Competencies

Core:

Problem-Solving: Strong analytical and problem-solving skills to identify and resolve issues. Ability to analyze complex problems, break them into smaller components and devise effective solutions using AI techniques. Analytical abilities to interpret data, identify patterns and make data-driven decisions.
Technical Expertise : Machine Learning and Deep Learning algorithms (regression, decision trees, neural networks) and libraries; Python, R, Java. Expertise in Data Analysis, statistical methods and data visualization tools; Software Engineering including but not limited to GitOps and CI/CD; Cloud Engineering and Computing (AWS, GCP, Redhat Openshift); Kubernetes, Containerization and Microservices.
Attention to Detail: High attention to detail to ensure code quality and functionality.

Support

Collaboration and Communication: Excellent collaboration and communication skills to work effectively with team members.
Adaptability: Ability to adapt to new technologies and tools quickly. Commitment to continuous learning and staying updated with the latest advancements in AI and machine learning
Time Management: Strong time management skills to handle multiple tasks and projects effectively.

Hiring Requirements

Graduate or graduating senior in Computer Science, Artificial Intelligence, Data Science, Software Engineering, or related quantitative field
Knowledgeable in Github profile
Experienced in at least one practical project involving Python and machine learning or GenAI (e.g., custom RAG chatbot, API integration, data pipeline, or ML model assignment)

Equal Opportunity Employer

Globe's hiring process promotes equal opportunity to applicants, Any form of discrimination is not tolerated throughout the entire employee lifecycle, including the hiring process such as in posting vacancies, selecting, and interviewing applicants.

Globe's Diversity, Equity and Inclusion Policy Commitment can be accessed here

Make Your Passion Part of Your Profession. Attracting the best and brightest Talents is pivotal to our success. If you are ready to share our purpose of Creating a Globe of Good, explore opportunities with us.

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