AI Intern, Data Engineering & Agent Workflows (Unpaid)

Armada is a leading provider of modular AI infrastructure, recognized for its innovative solutions. The AI Intern will work on building data infrastructure, AI agents, and automated workflows to support Armada's go-to-market strategy, focusing on data engineering and applied AI.

Responsibilities:

• Build and maintain data pipelines across Salesforce, SharePoint, Excel, and operational systems into our StarRocks data warehouse using dbt and Python
• Develop and ship AI agents and copilots using the Claude API (and other LLM tooling) for use cases like lead scoring, account research, call analysis, and internal Q&A over company data
• Design and automate cross-system workflows using Power Automate, Teams Adaptive Cards, and lightweight Python/FastAPI services to replace manual, spreadsheet-driven processes
• Model business data in dbt and Omni — building reusable semantic models, metrics, and dashboards that GTM, RevOps, and leadership rely on
• Enrich and clean prospect and account data using sources like ZoomInfo, LinkedIn Sales Navigator, and public government datasets (e.g., USASpending, SAM.gov, FCC, EIA, FERC, SEC EDGAR)
• Prototype and ship internal tools end-to-end — backend (Python/FastAPI), frontend (Vite/React), and storage (PostgreSQL, StarRocks) — for AI-prioritized daily workflows
• Write clear documentation for data models, pipelines, agents, and workflows so the team can extend and maintain them
• Collaborate with GTM, RevOps, Finance, and product teams to translate business questions into data and automation solutions
• Stay current on advances in agentic AI, retrieval, evals, and the modern data stack — and bring useful ideas back to the team

Requirements:

• Pursuing or recently completed a degree in Computer Science, Data Science, Data Engineering, Information Systems, Analytics, or a related field
• Strong Python skills, including experience with libraries like Pandas, requests, and FastAPI or Flask
• Solid SQL skills — able to write and debug analytical queries (joins, window functions, CTEs) against real-world, messy data
• Familiarity with the modern data stack (dbt, a columnar warehouse such as StarRocks/Snowflake/BigQuery/Databricks, and a BI tool such as Omni, Tableau, Looker, or Power BI)
• Hands-on experience building something with an LLM API (Claude, OpenAI, etc.) — even a side project counts. Familiarity with prompt design, tool/function calling, or RAG is a strong plus
• Exposure to workflow automation tools (Power Automate, Zapier, n8n, Airflow, or similar)
• Comfort with Git and basic software engineering practices (branches, PRs, code reviews)
• Strong problem-solving and analytical skills; able to work independently and in a team-oriented environment