DevOps Engineer

About Blitzy Blitzy is a Cambridge, MA based AI software development platform on a mission to revolutionize the software development life cycle by autonomously building custom software to unlock the next industrial revolution. We're transforming how enterprises build software, turning enterprise requirements into production-ready code with an agentic software development platform that can autonomously execute 80% of the quantum of software development work. We're backed by multiple tier 1 investors, and have proven success as founders of previous start-ups. Location: Cambridge, MA (HQ) Compensation: $150,000 - $180,000 + equity The Role 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 where your work directly shapes the reliability and performance of a platform used by Fortune 500 companies. What Success Looks Like - Kubernetes clusters are stable, well-documented, and capable of scaling to support growing AI agent workloads without manual intervention. - CI/CD pipelines are fully automated, reliable, and enabling engineering teams to ship faster with measurably fewer deployment failures. - Infrastructure provisioning is codified end-to-end in Terraform with zero manual steps required to spin up new environments. - Monitoring, alerting, and distributed tracing are in place across all production services — on-call is predictable, not chaotic. - Developer experience has been meaningfully improved: engineers spend less time waiting on infrastructure and more time building product. - AI agent orchestration infrastructure is robust, observable, and purpose-built to handle high-concurrency workloads at enterprise scale. Areas of Ownership - 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. Required Experience - 5–8 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 (AWS, Azure, or GCP). - Proficiency with Terraform for Infrastructure as Code. - Strong Linux administration skills and containerization expertise (Docker). What Makes You Stand Out - CKA (Certified Kubernetes Administrator) certification. - Experience with MLOps tooling such as MLflow, Kubeflow, or similar platforms. - Background in microservices architecture and service mesh technologies. - Familiarity with API gateway management and advanced service mesh configurations. - A bias for automation — if you've done something manually twice, you've already started scripting it. - Passion for AI infrastructure and excitement about building systems at the fron