[Hiring] DevOps Automation Engineer @Weekday AI

Role Description

We are seeking a highly skilled and automation-focused DevOps Automation Engineer to streamline engineering operations by replacing manual, repetitive, and error-prone processes with automated and AI-assisted workflows. This is a hands-on senior individual contributor role responsible for improving infrastructure management, CI/CD pipelines, security automation, and developer productivity across a cloud-native SaaS environment.

The ideal candidate will have strong experience with AWS, Infrastructure as Code (IaC), CI/CD automation, and production systems, combined with practical expertise in AI coding agents and agentic workflows. The role requires an engineering mindset, strong system troubleshooting capabilities, and the ability to critically review AI-generated code for correctness, security, and architectural consistency.

The engineer will collaborate closely with distributed teams in the United States and India, establish reusable automation standards, and ensure reliable, secure, and scalable software delivery.

Qualifications

• 3+ years of experience building and supporting production SaaS applications or platforms.
• Bachelor's degree in Computer Science, Information Technology, Engineering, or a related technical field, or equivalent practical experience.
• 2+ years of hands-on AWS experience with services such as EC2, ECS/EKS, S3, IAM, VPC, RDS, and CloudWatch.
• Production experience designing, implementing, and maintaining Infrastructure as Code using Terraform, OpenTofu, Pulumi, CloudFormation, CDK, or similar tools.
• Experience owning and maintaining production CI/CD pipelines using Jenkins, GitHub Actions, GitLab CI, CircleCI, Azure DevOps, or comparable tools.
• Strong knowledge of public cloud architecture, containerization, serverless computing, event-driven architecture, and RESTful API design.
• Proficiency in Python, Go, or a comparable programming language.
• Strong understanding of system design, distributed systems, failure handling, state management, idempotency, and infrastructure reliability.
• Demonstrated experience using AI coding agents for substantive implementation work, with the ability to review and validate generated outputs critically.
• Practical knowledge of generative AI tools, prompt engineering, agentic workflows, and AI-assisted productivity.
• Understanding of AI limitations, including hallucinations, context constraints, data sensitivity, and security risks.
• Strong troubleshooting, analytical, and problem-solving skills, including the ability to debug complex production systems and CI/CD pipelines.
• Excellent written communication and documentation skills.
• Ability to work effectively with distributed teams across time zones and attend late-evening meetings a few times per week.
• Must be legally authorized to work in the United States without current or future employer-sponsored visa support.
• Must reside within commuting distance of San Jose, California, or Albuquerque, New Mexico.
• Employment is contingent upon successful completion of a background check, including employment verification.

Requirements

• AWS
• Public Cloud
• Containerization

Good-to-Have Skills

• Google Cloud Platform (GCP)
• Microsoft Azure
• OpenTofu
• Terraform
• Jenkins
• SonarQube
• Docker and Kubernetes
• Infrastructure as Code
• CI/CD Automation
• AI Coding Agents and Agentic Workflows

Preferred Qualifications

• Experience with Terraform modules, state management, and infrastructure drift remediation.
• Hands-on experience with Jenkins shared libraries and reusable pipeline patterns.
• Familiarity with static analysis and security tools such as SonarQube, Snyk, Semgrep, Checkmarx, or CodeQL.
• Experience with observability tools such as CloudWatch, Datadog, Prometheus, Grafana, or OpenTelemetry.
• Knowledge of security and compliance automation, secrets management, policy as code, and SOC 2 audit evidence collection.
• Experience building internal developer platforms or self-service engineering tools.
• Background in cybersecurity, vulnerability management, or security-focused SaaS products.
• Experience coordinating engineering operations across onshore and offshore teams.

Key Success Measures

• Reduction in manual operational effort through automation.
• Improved CI/CD pipeline reliability, speed, and consistency.
• Infrastructure stability, security, and compliance.
• Reduction in recurring production and deployment incidents.
• Adoption of reusable automation tools and AI-assisted workflows.
• Improved developer productivity and platform usability.
• Quality and security of AI-generated code and infrastructure changes.
• Effective collaboration and operational alignment across distributed teams.