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.

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.

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

AI Intern, Data Engineering, Agent Workflows

Key skills