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 major cloud platforms (GCP, AWS, or Azure).
Proficiency with Terraform for Infrastructure as Code.
Strong Linux administration skills and containerization expertise (Docker).
Responsibilities
Build, manage, and scale Kubernetes clusters for AI agent workloads and production applications.
Design and implement robust CI/CD pipelines for application services and AI-driven workflows.
Automate infrastructure provisioning, scaling, and operations using Python and Terraform.
Deploy and maintain applications via Helm charts for consistency across environments.
Own the observability stack, including alerting, distributed tracing, and monitoring for production services and APIs.
Build and maintain infrastructure for AI agent orchestration to enable reliable, high-throughput execution.
Partner closely with engineering teams to enhance developer experience and operational tooling.
Continuously improve the security, reliability, and cost-efficiency of cloud environments.
Benefits
Opportunity to work with cutting-edge AI technology.
High-impact, hands-on role in a fast-moving environment.
Collaborative culture with close partnerships across engineering teams.
Focus on continuous improvement and innovation in infrastructure.
Location in a vibrant tech hub at Cambridge, MA.
Full Job Description
As a DevOps Engineer at Blitzy, you will be a critical force behind the infrastructure powering our cutting-edge AI agents and enterprise software development platform. Based out of our Cambridge, MA headquarters, you'll architect and maintain the scalable, resilient systems that enable Blitzy to autonomously deliver production-ready software at unprecedented speed. This is a high-impact, hands-on role for an engineer who thrives in a fast-moving environment and takes deep ownership of the systems they build.
Responsibilities
Build, manage, and scale Kubernetes clusters supporting AI agent workloads and production application deployments.
Design and implement robust CI/CD pipelines for both application services and AI-driven workflows.
Automate infrastructure provisioning, scaling, and operations using Python and Terraform.
Deploy and maintain applications via Helm charts, ensuring consistency across environments.
Own the observability stack: alerting, distributed tracing, and monitoring for all production services and APIs.
Build and maintain infrastructure for AI agent orchestration, enabling reliable and high-throughput agent execution.
Partner closely with engineering teams to improve developer experience, deployment strategies, and operational tooling.
Maintain and continuously improve the security, reliability, and cost-efficiency of our cloud environments.
Qualifications
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 major cloud platforms (GCP, AWS, or, Azure).
Proficiency with Terraform for Infrastructure as Code.
Strong Linux administration skills and containerization expertise (Docker).
