Senior Backend Infrastructure Engineer

Giga•San Francisco, CA

7d•$210,000 - $350,000•Onsite

About The Position

Giga has recently raised a $61M Series A and has several paying customers, including DoorDash. We’re building the next generation of customer experience — real-time AI agents that can understand emotion, resolve issues instantly, and scale across the world’s largest enterprises. It’s an exciting inflection point for the company. While we have been successful, we have larger ambitions. Our goal is to become the go-to AI platform for all enterprise automation, powered by our voice superintelligence. To achieve this, we need more great engineers. The work affects millions of people every day and our engineers have autonomy and make true impact. This opportunity is unique because we have brilliant founders, have found commercial success, and see a clear path to becoming a generational company. Some further info about us: Voice AI startup Giga raises $61M Series A DoorDash and Giga Partnership Giga builds AI agents trusted by the largest B2C companies in the world. Industry leaders like DoorDash trust Giga with their most complex support and operations workflows across voice, chat, and email. If being a part of this resonates with you, please apply! We're looking for an infrastructure engineer to build the platform that powers our AI agents. Your customers are other engineers on the team; you'll create the systems, tools, and abstractions that make everyone more productive and our platform more reliable. This isn't DevOps or traditional SRE. You'll write application code, but focused on the foundational layers: deployment systems, observability, data infrastructure, and the internal tools that let the team move fast without breaking things. As a senior infrastructure engineer, you'll own critical systems end-to-end and make decisions that affect the reliability and velocity of the entire engineering team.

Requirements

Have 4+ years of experience in infrastructure, platform, or backend engineering roles
Have built systems that other engineers depend on, and understand the responsibility that comes with that
Care deeply about reliability, but also know when "good enough" is the right call
Are comfortable across the stack, from application code to cloud infrastructure
Can debug production issues under pressure and build systems that prevent them from recurring
Think about developer experience as a product—you want the tools you build to be a pleasure to use
Are excited about the infrastructure challenges of running AI agents at scale

Responsibilities

Controlled deployments: Staged rollout systems with traffic scaling, scheduling, and pass rate thresholds to safeguard production
Observability: Creating the instrumentation, logging, and monitoring infrastructure that helps us understand what's happening in production
Data infrastructure: Building pipelines and storage systems for training data, analytics, and agent memory
Developer tooling: Internal CLIs, testing frameworks, and automation that reduces friction for the engineering team