Staff Application Engineer

Keystone AI•Bellevue, WA

1d•$225,000 - $245,000

About The Position

We are seeking a Staff Application Engineer to lead the frontend and application architecture for our decision-intelligence platform. In this end-to-end builder role, you will bridge Application Engineering, Product, Design, Science, and Customer Success to translate sophisticated data science and operations research into intuitive enterprise software.

Requirements

Proven experience building sophisticated production applications at a Staff level or equivalent depth.
Deep expertise in modern web tech stacks (React, TypeScript, JavaScript, HTML, CSS) and state management.
Solid software engineering fundamentals across APIs, testing, performance, observability, and production reliability.
Experience building data-intensive, analytical, scientific, or enterprise applications handling large datasets.
Strong product intuition, UX/interaction design judgment, and ability to shape ambiguous requirements into fluid workflows.
Familiarity with enterprise concerns including auth, permissions, security, and customer isolation.
Excellent technical communication, leadership, and mentorship capabilities in dynamic startup environments.

Nice To Haves

Experience with ML, forecasting, optimization, simulation, or decision science workflows.
Proficiency with data visualization tech (D3, SVG, Canvas, WebGL, Vega, Observable Plot).
Background in supply chain, manufacturing, logistics, or operations research domains.
Experience in Forward Deployment or client-embedded engineering environments.

Responsibilities

Architect, build, and maintain production web applications using React and TypeScript.
Define API contracts and system interfaces to deliver data-intensive science as a cohesive enterprise platform.
Transform statistical forecasts, optimization models, simulation outputs, uncertainty modeling, and scenario trade-offs into actionable, intuitive product features.
Establish modular, reusable frontend component libraries and application frameworks enabling scientific teams to launch new capabilities rapidly and scalably.
Uphold high standards for performance, accessibility, security, and data governance when handling large, complex enterprise datasets.
Partner with product, design, engineering, and clients to turn bespoke implementations into core product features.
Mentor engineers and establish architectural best practices.