Junior Data & Systems Developer

Kohn Pedersen Fox•New York, NY

5d•$70,000 - $90,000•Onsite

About The Position

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 motivated and technically curious Junior Data & Systems Developer to join our growing technology team. In this role, you will build and maintain data pipelines, manage databases, integrate third-party APIs, and develop lightweight internal tools and interfaces that support KPF's workflows. You will work closely with and directly support our AI Systems Engineer, helping to build and maintain the data infrastructure that powers KPF's AI systems. No prior AI experience is required, you will gain hands-on exposure to AI systems, including large language models, retrieval-augmented generation, and vector databases, through direct collaboration with our AI Systems Engineer. This is a role where you'll build real AI skills on the job. This is an entry-to-junior level role (0 – 4 years’ experience,) and we are looking for someone who is eager to learn, has foundational hands-on experience, and is ready to grow within a collaborative and design-forward environment. You don't need to know everything, but you need to be resourceful, dependable, and excited about building things that make a difference.

Requirements

Python — comfortable writing scripts, automating tasks, and building small applications
SQL — ability to write and optimize queries; experience with relational databases (MSSQL, PostgreSQL, MySQL, or SQLite)
REST APIs — experience consuming APIs, handling JSON responses, and building simple integrations
Flask or FastAPI — some experience building basic web applications or API endpoints
AWS basics — familiarity with EC2, S3, and RDS; ability to deploy and manage simple cloud resources
Docker — basic understanding of containerization and ability to build and run Docker containers
Git — version control fundamentals; comfortable working in a collaborative codebase

Nice To Haves

Experience with data pipeline tools (n8n, or similar schedulers)
Familiarity with AWS Lambda or other serverless compute
Basic frontend skills — HTML, CSS, JavaScript or lightweight frameworks (React, Vue)
Exposure to data visualization tools or libraries (D3, Chart.js, etc.)
Familiarity with CI/CD pipelines (GitHub Actions, etc.)
Basic familiarity with LLMs and AI concepts (how data feeds into AI systems, embeddings, vector search)
Exposure to vector databases (Azure AI Search) — even conceptual understanding is a plus
Curiosity about AI/ML systems and eagerness to grow into more AI-focused work
Interest or background in AEC (Architecture, Engineering & Construction) or creative industries
Experience working with AI coding tools like Claude Code, Cursor or GitHub Copilot.

Responsibilities

Data Pipelines & Data Management Build, maintain, and monitor ETL/ELT data pipelines to collect, transform, and load data from various internal and external sources
Clean, validate, and structure data to ensure quality and consistency across systems
Manage and maintain relational databases (MSSQL, PostgreSQL, MySQL, or similar), including schema design, indexing, and query optimization
Write efficient, well-structured SQL queries for data extraction, transformation, and reporting
Document data flows, schemas, and pipeline logic for team reference
API Integration Connect to and consume third-party and internal REST APIs to pull, sync, and process data
Build lightweight API wrappers and integrations in Python to automate data collection workflows
Handle authentication, pagination, rate limiting, and error handling in API integrations
Monitor and maintain existing integrations to ensure reliability and data freshness
Web Development & Internal Tools Develop simple internal web applications and dashboards using Flask or FastAPI
Build basic frontend interfaces (HTML/CSS/JavaScript or lightweight frameworks) to expose data and tools to internal users
Collaborate with team members to understand needs and iterate on practical, easy-to-use tools
Maintain and improve existing internal applications
Cloud Deployment & Infrastructure Deploy applications and services on AWS using core services such as EC2, S3, and RDS
Containerize applications using Docker and manage basic container deployments
Follow best practices for environment configuration, secrets management, and basic security
AI Systems Support (On-the-Job Training & Growing Responsibility) Prepare, clean, and structure data for ingestion into AI and LLM pipelines (e.g., document chunking, metadata tagging, embedding-ready formatting)
Maintain and monitor vector store data ingestion pipelines (e.g., design workflows to upload data and documents, refresh indexes)
Support the AI Systems Engineer with data tasks related to RAG (Retrieval-Augmented Generation) systems
Help manage knowledge bases and structured data sources that feed conversational AI tools
Assist with testing and validating data quality within AI-powered applications