Senior DevOps Engineer

Blitzy•Cambridge, MA

8d•$160,000 - $230,000•Onsite

About The Position

Blitzy is hiring a hands-on DevOps Engineer to build and maintain the infrastructure that powers its AI agents and enterprise software development platform. Based at the company’s Cambridge, Massachusetts headquarters, the engineer will architect and maintain scalable, resilient systems that support autonomous production software delivery. This is a high-impact role in a fast-moving environment that calls for strong ownership of the systems built. The position works closely with engineering teams to improve developer experience, deployment strategies, and operational tooling. Blitzy describes its culture as fast-moving, collaborative, focused on high standards and invention, and centered on delivering value to customers. Compensation is $160,000–$230,000 plus bonus and equity. Blitzy is an equal opportunity employer committed to building a diverse and inclusive team. Individual pay depends on factors including skills, experience, education, and training.

Requirements

At least 5 years of DevOps or infrastructure engineering experience in production environments.
Deep expertise in Kubernetes, including deployment, scaling, networking, and troubleshooting.
Strong Python proficiency for automation, scripting, and tooling.
Hands-on experience with Helm for application package management.
Proven track record designing and maintaining CI/CD pipelines.
Experience with a major cloud platform: GCP, AWS, or Azure.
Proficiency with Terraform for Infrastructure as Code.
Strong Linux administration skills and containerization expertise, including Docker.

Responsibilities

Build, manage, and scale Kubernetes clusters for AI agent workloads and production application deployments.
Design and implement CI/CD pipelines for application services and AI-driven workflows.
Automate infrastructure provisioning, scaling, and operations using Python and Terraform.
Deploy and maintain applications with Helm charts to ensure consistency across environments.
Own observability for production services and APIs, including alerting, distributed tracing, and monitoring.
Build and maintain infrastructure for AI agent orchestration to support reliable, high-throughput agent execution.
Partner with engineering teams to improve developer experience, deployment strategies, and operational tooling.
Continuously improve the security, reliability, and cost-efficiency of cloud environments.