Full Stack Engineer – Cloud & SaaS Integrations

Full Stack Engineer – Cloud & SaaS Integrations

Overview

Cloud spend is no longer limited to AWS, Google Cloud, and Azure. Our customers now run a large and growing share of their technology spend through SaaS platforms, data clouds, and AI vendors. Every one of those vendors represents an integration that brings another slice of their spend into view.

Key Responsibilities

• Build new integrations. Design and ship integrations against third-party billing and usage APIs, including authentication, incremental sync, rate limits, error handling, and schema drift. Invest in the Integrations Framework, testing harnesses, and scaffolding so each new integration requires less effort than the last. Work in an AI-Augmented Engineering Environment. Use AI daily to explore unfamiliar codebases and third-party APIs, prototype approaches, generate and review code, debug, write tests, and produce documentation. Evaluate where agentic tooling can increase velocity and where human judgment must maintain the quality bar. Own the Integration Management Experience. Build the interfaces customers use to connect, configure, and trust their integrations. Provide health and status visibility, actionable error states, credential and key rotation, and clear feedback when attention is required. Design for Self-Service. Build self-service capabilities into the framework from the start, including backfills, diagnostics, health visibility, and API-first workflows that support both human and agent-driven use cases. Deliver End to End

Qualifications

• At least 3 years of professional software engineering experience shipping and owning production features. Strong TypeScript skills, including modern frontend development; React is preferred. Hands-on Go experience, or strong backend experience with Python, Java, Node.js, or C# and enthusiasm for learning Go. Experience designing and consuming REST APIs and integrating complex third-party APIs. Ability to work across the stack and own features from the database through the user interface. Working proficiency in SQL. Experience developing cloud solutions or using GCP, AWS, or Azure. Experience using AI tools throughout the engineering workflow. Strong knowledge of software engineering practices, design patterns, and architectural principles. Demonstrated interest in building high-quality web and SaaS applications. Excellent written and verbal English communication skills. Self-organized, goal-oriented, self-motivated, confident, thorough, and tenacious.