Data & Systems Developer Intern

Location: New York

** KPF
* * is a global architecture and urban design firm known for its innovative approach to the built environment. We are committed to integrating cutting-edge technology into our design process, and we are building an internal data and systems capability to enhance how we work, collaborate, and deliver world-class architecture.
** Role Overview
** We are looking for a curious and motivated
** Data & Systems Developer Intern
** to join our technology team for a summer or semester engagement. In this role, you will get hands-on experience building data pipelines, working with APIs, developing lightweight internal tools, and supporting the infrastructure that powers KPF's AI systems.

You will work closely with our
** AI Systems Engineer
** and
** Junior Data & Systems Developer**, contributing to real projects from day one. This is not a passive internship — you will write real code, work with real data, and build things that are actually used.

You will gain hands-on exposure to AI systems, including large language models, retrieval-augmented generation, vector databases, and agentic tools through direct collaboration with our team. This is a role where you'll build real, marketable AI and data engineering skills on the job.
** What You'll Work On
**** Data Pipelines & Data Management
*** Assist in building and maintaining
** ETL/ELT data pipelines
** to collect, transform, and load data from internal and external sources
* Help clean, validate, and structure data to ensure quality and consistency across systems
* Write
** SQL queries
** to extract, transform, and report on data from relational databases (MSSQL, PostgreSQL, MySQL, or similar)
* Help document data flows, schemas, and pipeline logic
** API Integration
*** Connect to and consume
** REST APIs
** to pull and process data
* Assist in building lightweight
** Python scripts and integrations
** to automate data collection workflows
* Learn to handle authentication, pagination, rate limiting, and error handling in API integrations
** Web Development & Internal Tools
*** Contribute to simple
** internal web applications and dashboards
** built with
** Flask
* * or
** FastAPI
* ** Help build basic frontend interfaces (HTML/CSS/JavaScript) to expose data and tools to internal users
* Collaborate with team members to understand needs and iterate on practical solutions
** Cloud & Infrastructure Basics
*** Get hands-on experience deploying on
** AWS
* * using core services such as
** EC2, S3, and RDS
*** Learn to containerize applications using
** Docker
* ** Follow best practices for environment configuration and basic security
** AI Systems Exposure *(Learning Opportunity)
**** Assist in preparing and structuring data for ingestion into
** AI and LLM pipelines** (e.g., document chunking, metadata tagging, embedding-ready formatting)
* Help maintain
** vector store
** data ingestion workflows (uploading documents, refreshing indexes)
* Support the team with data tasks related to
** RAG (Retrieval-Augmented Generation)
** systems* Gain exposure to
** knowledge bases
** and structured data sources that feed conversational AI tools
* Assist with testing and validating data quality within AI-powered applications
** What We're Looking For
**** Must-Have**
* ** Python** — basic to intermediate proficiency; comfortable writing scripts and small programs
* ** SQL** — ability to write queries; some experience with relational databases
* ** REST APIs** — basic understanding of how APIs work; some experience consuming them
* ** Git** — basic version control; comfortable committing and collaborating on a shared codebase
* ** Currently enrolled
** in a Bachelor's or Master's program in Computer Science, Information Systems, Data Science, or a related field
** Nice-to-Have
*** Any exposure to
** Flask or FastAPI** — even a course project counts
* Basic familiarity with
** AWS
* * or any cloud platform
* Some experience with
** Docker
* * or containerization concepts
* Exposure to
** data visualization
** tools or libraries (D3, Chart.js, etc.)
* Basic familiarity with
** LLMs and AI concepts** (embeddings, vector search, RAG)
* Experience with
** AI coding tools
** like Claude Code, Cursor, or Git Hub…