Collaboration — partner with stakeholders to scope the right tool for the job, with analytics engineers to shape the underlying data models, and with data engineers on platform constraints
YOUR EXPERIENCE INCLUDES
5+ years building production software, with meaningful time spent on full-stack web applications
Strong Python — APIs (FastAPI, Flask, or similar), data access patterns, packaging, testing
TypeScript/React (or comparable framework), component design, interactive data UIs
Hands-on experience with GCP application services — App Engine, Cloud Run, GKE, IAM
Strong SQL and comfort working with cloud data warehouses (BigQuery in our case) — you can write a query, understand its cost, and design an app’s data access layer around it
Experience developing and deploying AI/LLM-powered applications in production — prompt design, structured output, evaluation, cost/latency tradeoffs, awareness that the model and tooling landscape changes quickly
Experience operating what you ship — logging, monitoring, error handling, debugging in production
Experience with software engineering best practices: CI/CD, automated testing, observability, secure application design
Bachelor’s degree in Computer Science, Engineering, or equivalent practical experience
NICE TO HAVE
Experience building AI-native applications such as text-to-SQL interfaces, copilots, agentic workflows, or automated insight-generation systems
Hands-on experience with one or more LLM provider APIs (Anthropic’s Claude, OpenAI, Google, open-weight models, etc.) and agent frameworks (Claude Agent SDK, LangGraph, or similar)
Experience with managed AI/ML platforms (Vertex AI, SageMaker, or similar) — model serving, embeddings, evaluation tooling
Familiarity with dbt and modern data warehouse patterns from a consumer’s perspective
Experience with Airflow for triggered jobs and background work
Familiarity with Terraform for managing application infrastructure
Background designing data-heavy UIs — tables, drill-downs, large result sets, interactive exploration
Prior experience as the first or only application engineer on a data team — comfort owning the full lifecycle