About the job
About Giga
Giga has recently secured a remarkable $61M in Series A funding and is already serving several notable clients, including DoorDash. Our mission is to revolutionize customer experience through cutting-edge real-time AI agents that comprehend emotions, address issues instantaneously, and scale to meet the demands of the world’s largest enterprises.
We are at a pivotal moment in our journey. While we have achieved early success, our aspirations extend far beyond. Our vision is to establish ourselves as the leading AI platform for enterprise automation, driven by our voice superintelligence. To realize this ambition, we are on the lookout for exceptional engineers.
The impact of our work touches millions of lives daily, and our engineers enjoy the autonomy to make a significant difference. This role is particularly unique due to our visionary founders, proven commercial success, and a clear trajectory towards becoming a generational company. Here are some key highlights about us:
At Giga, we create AI agents that are trusted by some of the largest B2C companies globally. Industry giants like DoorDash rely on Giga to manage their most complex support and operational workflows across voice, chat, and email. If you resonate with this mission, we encourage you to apply!
The Role
We are seeking a seasoned infrastructure engineer who will construct the foundational platform that empowers our AI agents. Your primary users will be fellow engineers; your role will involve developing systems, tools, and abstractions that enhance productivity and ensure the reliability of our platform.
This position transcends traditional DevOps or SRE roles. You will be responsible for writing application code with a focus on core infrastructure components: deployment systems, observability frameworks, data infrastructure, and the internal tools that enable our team to innovate swiftly and safely.
What You'll Work On
Here are a few key priorities that you will tackle:
Controlled deployments: Develop staged rollout systems with traffic scaling, scheduling, and pass rate thresholds to safeguard production environments.
Observability: Establish the instrumentation, logging, and monitoring frameworks that provide insights into production dynamics.
Data infrastructure: Design and implement robust data pipelines and storage solutions.

