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.
Nice to have
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
Full description
**This role is for one of Weekday’s clients Salary range: Rs 2000000 - Rs 3000000 (ie INR 20 - 30 LPA)**
Min Experience: 3+ years Location: Remote (India), India JobType: full-time
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.
Requirements
Roles & Responsibilities
1. DevOps Automation & Process Optimization
Identify manual, repetitive, and error-prone operational activities across development, deployment, infrastructure, and security workflows.
Design and implement automated, AI-assisted workflows to improve engineering efficiency and reduce operational overhead.
Measure automation outcomes, including time saved, reduced manual effort, and improvements in delivery reliability.
Develop reusable automation scripts, tools, templates, and workflows that can be adopted across engineering teams.
2. Infrastructure as Code & Cloud Management
Design, implement, and maintain infrastructure using Terraform and other Infrastructure as Code tools where appropriate.
Develop reusable infrastructure modules and establish effective state management, environment promotion, drift detection, and remediation practices.
Manage and troubleshoot AWS services across compute, networking, storage, identity and access management, and databases.
Ensure infrastructure reliability, scalability, security, and resilience under failure conditions.
Apply strong system design principles, considering failure domains, state management, idempotency, and blast radius.
3. CI/CD Pipeline Development
Own, extend, and optimize CI/CD pipelines across build, testing, security scanning, artifact management, and deployment stages.
DevOps Automation Engineer at weekday-1 (Remote) — aijobsearch
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.
AWS
Public Cloud
Containerization
Develop reusable pipeline patterns and shared libraries to standardize software delivery.
Integrate automated quality checks and security controls into development and deployment workflows.
Configure and optimize SonarQube quality gates to identify meaningful code quality and security issues while minimizing unnecessary alerts.
Troubleshoot pipeline failures and improve deployment consistency, speed, and reliability.
4. AI-Assisted Engineering & Agentic Automation
Use AI coding agents, such as Claude Code, as a primary implementation tool for engineering and automation tasks.
Break down complex requirements into clear specifications, provide appropriate context and guardrails, and guide AI agents through implementation.
Critically review AI-generated code and specifications for hallucinations, security vulnerabilities, architectural inconsistencies, and functional correctness.
Design and implement multi-step agentic workflows with appropriate human-in-the-loop validation.
Integrate generative AI tools with internal data sources, APIs, and enterprise systems where appropriate.
Build reusable AI skills, templates, agent configurations, and automation workflows for shared team use.
Apply responsible AI practices, including prompt injection awareness, data sensitivity controls, sandboxed execution, and output validation.
5. Production Reliability & Incident Management
Investigate and resolve production incidents, infrastructure failures, and CI/CD pipeline issues using a systematic, evidence-driven approach.
Perform root cause analysis and implement preventive measures to reduce recurring incidents.
Develop and maintain operational runbooks, troubleshooting guides, and technical documentation.
Improve system observability, monitoring, alerting, and operational readiness.
Drive continuous improvements in application stability, deployment reliability, and infrastructure performance.
6. Security & Quality Engineering
Apply secure-by-design principles across infrastructure, automation, and software delivery processes.
Integrate security scanning, code quality checks, and compliance controls into CI/CD pipelines.
Collaborate with security teams to translate vulnerability and threat intelligence into practical platform capabilities.
Support secrets management, policy-as-code initiatives, and automated compliance evidence collection where applicable.
Maintain high standards of testing, version control, modularity, code review, and maintainable engineering practices.
7. Cross-Functional Collaboration
Collaborate with engineering, product, security, and operations teams to identify requirements and implement automation solutions.
Work closely with distributed teams in the United States and India to align technical standards, ownership, operational practices, and handoffs.
Participate in scheduled evening meetings to maintain effective collaboration with India-based teams.
Evaluate existing tools and recommend improvements based on reliability, usability, cost, and engineering efficiency.
Plan and execute tool migrations through structured, well-communicated stages that minimize disruption to developers.
Document systems and workflows clearly to support maintainability and collaboration across time zones.
Requirements & 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.
Must-Have Skills
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.