About the role

We're looking for an AI Intern to help design and implement practical AI workflows that automate business processes and improve analytics. You'll evaluate AI tools, build prototypes, connect APIs, and create dashboards that deliver measurable impact across teams. This is a hands-on role for a curious problem solver who enjoys experimenting, documenting, and shipping working automations.

What you'll do

Map manual processes and design AI-enabled workflows to reduce time, cost, and errors.
Evaluate and compare AI tools and platforms (e.g., OpenAI/Azure OpenAI, Google Vertex AI, LangChain, Zapier/Make, RPA tools).
Build lightweight prototypes: data pipelines, API integrations, webhooks, and automation scripts (primarily in Python).
Develop analytics dashboards and reports (e.g., Power BI/Tableau/Looker) to track outcomes of automations.
Implement LLM use cases (prompting, basic RAG, embeddings) with attention to data quality and security guidelines.
Document experiments, build how-to guides, and share results with non-technical stakeholders.
Monitor performance, run A/B tests, and iterate to improve accuracy, latency, and cost.
Collaborate with business teams (Ops, Marketing, HR, Finance) to translate needs into solutions.

What you'll learn

End-to-end automation: from discovery to production and measurement.
Practical LLM integration patterns, prompt engineering, and evaluation.
Best practices for data governance, privacy, and model/tool selection.
Experiment design, rapid prototyping, and ROI measurement.

Minimum qualifications

Currently pursuing a degree in Computer Science, Data Science, Engineering, or related field (or equivalent experience).
Comfortable with Python and basic SQL; familiarity with APIs and JSON.
Understanding of ML/AI fundamentals (classification vs. generation, evaluation, basic statistics).
Strong problem-solving, documentation, and communication skills.
Ability to work 20–40 hours/week for 10–12 weeks (flexible).

Nice to have

Experience with Zapier/Make or RPA (UiPath/Automation Anywhere/Power Automate).
Familiarity with LLM frameworks (LangChain/LlamaIndex), vector databases (FAISS/Pinecone/Chroma).
Cloud basics (AWS/GCP/Azure), Docker, Git.
Analytics tools (Tableau/Power BI/Looker/Metabase) and data wrangling (Pandas).
Frontend for prototypes (Streamlit/Gradio) is a plus.

AI Automation & Analytics Intern