Infrastructure & Reliability Software Engineer, CrewAI

• 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

Desirable

• You'll build and operate the platform infrastructure behind CrewAI's cloud and enterprise deployments
• You'll work across multiple hyperscalers - AWS, Azure, and GCP
• You’ll work on containers, CI/CD, deployment automation, observability, secrets, networking, and runtime reliability. Your job is to make the product and runtime teams faster while making customer’s production environments safer
• This is not a pure DevOps support role. You'll write code, improve systems, design deployment paths, harden production, and build the internal platform that lets CrewAI scale and scale our customer deployments
• 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 - and 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