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AI Intern, Data Engineering, Agent Workflows

Location

United States

Posted

50 days ago

Salary

0

Seniority

Entry Level

Job Description

AI Intern, Data Engineering, Agent Workflows

Armada

• 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.

Job 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.

Benefits

  • Hands-on experience working with modern AI, automation, and data engineering tools in a real-world business environment
  • Exposure to cutting-edge technologies including LLMs, workflow automation, and cloud data platforms
  • The opportunity to build impactful projects used by GTM, RevOps, Finance, and leadership teams
  • Mentorship and collaboration with experienced engineers and business leaders
  • Practical experience with Python, SQL, dbt, APIs, dashboards, and AI-powered workflows
  • A stronger technical portfolio and resume through meaningful, production-focused projects
  • Insight into how AI and data systems drive decision-making and operational efficiency in a fast-growing technology company
  • Professional development in problem-solving, communication, collaboration, and cross-functional teamwork

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