Build and operate the infrastructure foundation for CrewAI's multi-agent AI platform across AWS, Azure, and GCP. Own CI/CD, observability, reliability, security, and self-hosted deployment tooling for cloud and enterprise environments.
Salary not listed
On-site5+ YOEDevOps / SRE
About the role
Responsibilities
Own and improve the infrastructure that runs CrewAI's platform: AWS, ECS/ECR, Docker, Kubernetes/Helm, networking, secrets, databases, Redis, and related services.
Build and maintain CI/CD pipelines for build, test, image publishing, migrations, environment promotion, rollbacks, and deploy safety.
Improve reliability across cloud and enterprise deployments: health checks, alerting, incident response, capacity planning, recovery paths, and operational runbooks. Own the front-line on-call rotation and its SLAs.
Partner with runtime engineers on Celery/FastAPI/Redis workloads and with product engineers on Rails/Solid Queue/Postgres production behavior.
Manage production observability and telemetry infrastructure: logs, metrics, traces, dashboards, Sentry/OpenTelemetry plumbing, actionable alerts, and telemetry export to customers' own monitoring systems.
Harden security and compliance posture across IAM, workload identity, secrets management, vulnerability scanning, dependency/image hygiene, and least-privilege access.
Build the tooling and automation that lets field engineers and customers run self-hosted installs themselves - Helm charts, environment config, release artifacts, pre-flight checks, and install runbooks - so engineering does fewer hands-on installs over time.
Reduce operational toil by automating recurring workflows and making deployments boring.
Requirements
Strong infrastructure/platform engineering experience in production SaaS environments.
Deep practical experience with AWS, Docker, CI/CD, GitHub Actions, and containerized services.
Experience with ECS and/or Kubernetes; Helm experience is a strong plus.
Comfort operating PostgreSQL, Redis, background job systems, queues, and web services in production.
Strong debugging instincts across app, infra, network, deploy, and dependency layers.
Security-minded approach to IAM, secrets, workload identity, vulnerability management, and production access.
Ability to write reliable automation in Python, Ruby, Go, Bash, or similar.
Calm, rigorous approach to incidents, rollbacks, migrations, and production change management.
Nice-to-Haves
Experience with AI/agent platforms, workflow runtimes, or high-volume async execution systems.
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