Database Reliability Engineer

This is a fully remote position, open to applicants in United States.

📋 Description

• Ensure database reliability across platforms such as PostgreSQL, MySQL, MongoDB, Redis, ScyllaDB, Aerospike, and managed cloud services.

• Facilitate high availability, replication, partitioning, storage management, and connection management.

• Create Kubernetes operators, implement infrastructure as code, develop GitOps workflows, and enhance production tooling using Go or Python.

• Streamline automation for provisioning, failover, backups, schema migrations, and lifecycle management.

• Develop self-healing, fault-tolerant infrastructure alongside internal tools to minimize operational toil.

• Improve database performance and cost-efficiency across both cloud and on-premises environments.

• Assist in capacity planning, resource efficiency, storage optimization, workload consolidation, and performance tuning.

• Collaborate with application engineering teams on schema evaluations, migration strategies, query optimization, connection management, and zero-downtime deployments.

• Utilize AI for observability, anomaly detection, root cause analysis, documentation, predictive insights, and code assessment.

⛳️ Requirements

• Minimum of 2 years of experience in Database Reliability Engineering, Database Platform Engineering, Site Reliability Engineering, or a similar infrastructure engineering role with a strong emphasis on databases.

• Experience in supporting at least one major relational database, ideally Aurora MySQL.

• Operational expertise with PostgreSQL, MongoDB, ScyllaDB, Aurora, or other managed cloud database services.

• Experience in building and managing stateful Kubernetes workloads utilizing StatefulSets, Persistent Volumes, database operators, Terraform, Pulumi, FluxCD, ArgoCD, GKE, or EKS.

• Hands-on software development experience with Go or Python for automation, platform tooling, Kubernetes controllers, APIs, and infrastructure.

• Familiarity with observability, monitoring, service level objectives, capacity planning, performance optimization, and self-service engineering solutions.

• Practical experience with AI tools such as Claude, GitHub Copilot, Cursor, MCP, or comparable technologies.

• Strong engineering judgment to evaluate AI-generated outputs for reliability and security.

• May need to obtain a gaming license issued by the relevant state agency as a condition of employment.

🏝️ Benefits

• Bonus

• Equity

• Applicable benefits

• Support throughout the gaming license process if necessary

• Option for remote work within the US