AI Intern, Data Engineering & Agent Workflows (Unpaid)

About the CompanyArmada is the hyperscaler for the edge, delivering modular AI infrastructure from first deployment to AI factory with speed, scale and sovereignty. Named one of Fast Company's Most Innovative Companies and to the CNBC Disruptor 50, Armada’s solutions are deployed in over 60 countries globally for organizations ranging from energy to defense. With nearly half a billion dollars in funding, Armada is backed by top investors such as Microsoft (M12), Founders Fund, and BlackRock, and has collaborations and partnerships including NVIDIA, Palantir and Dell Technologies. We are looking for the most brilliant minds in the world to join us. Working at Armada means taking ownership, driving autonomy, and delivering impact. You’ll tackle challenges that haven’t been solved before and help build something transformative from the ground up. What you do here will not only define your career but help further Armada’s mission to bridge the digital divide for customers around the world.About the role:We are seeking a motivated AI Intern to join the Data & AI Agent team and help build the data infrastructure, AI agents, and automated workflows that power Armada's go-to-market motion. This is a hands-on role focused on data engineering and applied AI — not traditional ML research. You'll work directly with the Head of Data and AI Agent on the systems that turn fragmented Salesforce, SharePoint, and operational data into a single source of truth, and on the AI-powered tooling (lead scoring, signal intelligence, internal copilots) that runs on top of it.We are seeking a motivated Intern (unpaid) to join our team. This unpaid internship program is tailored for engineering students seeking to enrich their academic learning with practical, hands-on experience in the field.Location:This role is remote. Key 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.Qualifications: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.What You’ll Gain:Hands-on experience working with modern AI, automation, and data engineering tools in a real-world business environmentExposure to cutting-edge technologies including LLMs, workflow automation, and cloud data platformsThe opportunity to build impactful projects used by GTM, RevOps, Finance, and leadership teamsMentorship and collaboration with experienced engineers and business leadersPractical experience with Python, SQL, dbt, APIs, dashboards, and AI-powered workflowsA stronger technical portfolio and resume through meaningful, production-focused projectsInsight into how AI and data systems drive decision-making and operational efficiency in a fast-growing technology companyProfessional development in problem-solving, commu