DevOps Engineer III

Job Responsibilities:

• Design, build, maintain, and enhance complex CI/CD pipelines using Jenkins, GitHub Actions, Azure DevOps, or similar tools.
• Implement reusable pipeline libraries, templates, quality gates, security scanning, automated testing, packaging, and deployment workflows.
• Implement and support GitOps-based deployment workflows using Argo CD, Flux, or equivalent technologies.
• Maintain declarative application and platform configuration, automated reconciliation, environment promotion, drift detection, rollback, RBAC, and secrets integration.
• Implement deployment strategies such as blue/green, canary, progressive delivery, and automated rollback where appropriate.
• Troubleshoot complex CI/CD, GitOps, and deployment issues and implement permanent corrective solutions.

• Implement and improve scalable, secure, resilient, and cost-efficient infrastructure primarily in AWS.
• Work with AWS services including EC2, ECS, EKS, IAM, VPC, ALB/NLB, S3, RDS, Route 53, CloudWatch, SSM, Lambda, and related platform services.
• Troubleshoot complex infrastructure, networking, IAM, DNS, security, performance, and application connectivity issues.
• Implement established cloud architecture, security, tagging, governance, reliability, and operational standards.
• Contribute implementation expertise, technical options, and proof-of-concept validation during solution and design reviews.

• Design, develop, test, and maintain reusable infrastructure using Terraform/OpenTofu.
• Create and enhance modular IaC frameworks used across multiple products, environments, and AWS accounts.
• Implement Terraform state management, testing, validation, versioning, and lifecycle practices.
• Integrate infrastructure provisioning with CI/CD and GitOps workflows.
• Troubleshoot complex Terraform plan/apply issues, state issues, drift, and dependency problems.
• Participate in and provide technical feedback during peer reviews of Infrastructure as Code changes.

• Develop automation and platform tooling using Python, Go, PowerShell, Bash, TypeScript, Ansible, or equivalent technologies.
• Build reusable automation, APIs, utilities, templates, and workflows that reduce manual engineering and operational activities.
• Implement Internal Developer Platform capabilities and self-service workflows based on established platform architecture and standards.
• Build and improve paved roads/golden paths that simplify infrastructure provisioning and application delivery.
• Maintain and improve artifact repository, configuration-management, and engineering automation capabilities.

• Build, configure, operate, and improve Kubernetes platforms, particularly Amazon EKS and Azure AKS where applicable.
• Implement standards for cluster configuration, networking, workload isolation, identity, security, scaling, storage, observability, and lifecycle management.
• Build and maintain reusable Helm charts and Kubernetes deployment patterns.
• Troubleshoot complex Kubernetes, container, networking, storage, identity, resource, and application deployment issues.
• Automate Kubernetes provisioning, upgrades, configuration, and operational activities.

• Implement monitoring, logging, metrics, tracing, dashboards, and alerting using Datadog, Grafana, Prometheus, CloudWatch, or similar platforms.
• Lead troubleshooting and root-cause analysis for complex infrastructure, platform, CI/CD, and deployment issues.
• Implement high-availability, resiliency, disaster-recovery, scalability, and performance patterns defined for platform workloads.
• Identify recurring operational issues and implement automation or permanent corrective actions.
• Create and improve operational runbooks, health checks, recovery procedures, and platform documentation.
• Participate in an on-call rotation where applicable.

• Apply AI and agentic capabilities to practical DevOps and Platform Engineering use cases, including automation, CI/CD, troubleshooting, incident analysis, documentation, and developer self-service.
• Build or integrate AI-enabled workflows using approved enterprise AI services such as Amazon Bedrock, Azure OpenAI/OpenAI, or equivalent platforms.
• Implement secure integrations between AI capabilities and approved cloud services, APIs, repositories, and engineering tools.
• Apply appropriate identity, authorization, observability, guardrails, cost controls, and human-in-the-loop mechanisms to AI-enabled automation.

• Provide technical guidance within Platform Engineering initiatives and lead defined technical workstreams when required.
• Mentor engineers and share expertise across cloud, DevOps, GitOps, Kubernetes, automation, and platform engineering practices.
• Participate in design, code, infrastructure, and operational-readiness reviews and provide actionable technical feedback.
• Collaborate with architects and senior engineers to evaluate implementation approaches and architectural trade-offs.
• Partner with Engineering, Platform, CloudOps, SRE, Security, and other teams to deliver reliable platform capabilities.

Required Skills & Experience:

• 7+ years of experience in DevOps, Cloud Engineering, Platform Engineering, SRE, Infrastructure Engineering, Software Engineering, or a related role.
• Strong hands-on experience with AWS and enterprise cloud infrastructure.
• Advanced experience with Terraform/OpenTofu and Infrastructure as Code, including reusable modules and multi-environment implementations.
• Strong experience designing, building, and troubleshooting CI/CD pipelines using Jenkins, GitHub Actions, Azure DevOps, or equivalent platforms.
• Strong hands-on experience with GitOps deployment tools such as Argo CD, Flux, or equivalent technologies.
• Strong hands-on experience with Docker, Kubernetes, EKS and/or AKS, and Helm.
• Experience with configuration management and automation using Ansible or equivalent technologies.
• Strong scripting/programming skills using one or more of Python, Go, PowerShell, Bash, TypeScript, or equivalent languages.
• Experience with Git and pull-request-based development workflows.
• Strong understanding of IAM/RBAC, cloud security, networking, DNS, load balancing, VPCs/subnets, routing, and security groups/firewalls.
• Experience with observability platforms such as Datadog, Grafana, Prometheus, CloudWatch, or equivalent tools.
• Ability to independently troubleshoot complex infrastructure, Kubernetes, CI/CD, GitOps, and deployment issues.
• Demonstrated experience mentoring engineers and providing technical guidance.

Preferred Skills :

• Experience building or contributing to Internal Developer Platforms and developer self service capabilities.
• Experience with multi-account AWS environments and enterprise cloud governance.
• Experience with Azure and AKS or other multi-cloud infrastructure.
• Experience with AI/LLM platforms and agentic automation, including Amazon Bedrock, Azure OpenAI/OpenAI, or equivalent technologies.
• Experience with policy-as-code, security scanning, SonarQube, Trivy, or similar engineering controls.
• Experience with cloud cost optimization and FinOps practices.
• AWS, Terraform, Kubernetes, or other relevant certifications are a plus.
• Experience working in an Agile/Scrum environment.

Key Competencies:

• Strong technical troubleshooting and problem-solving skills.
• Automation-first and platform-engineering mindset.
• Ability to independently own complex technical requirements from design through implementation and operational readiness.
• Ability to translate architecture and engineering standards into reliable production implementations.
• Ability to mentor engineers and lead defined technical workstreams without formal people-management responsibility.
• Strong collaboration skills across Engineering, Platform, CloudOps, SRE, Security, and Architecture teams.
• Good written and verbal communication skills and ability to explain technical trade-offs.
• Continuous-learning mindset and ability to evaluate emerging technologies through hands-on implementation.

• Independently own and deliver complex DevOps and Platform Engineering work.
• Design and implement advanced CI/CD and GitOps workflows using established enterprise standards.
• Build and enhance reusable Terraform/OpenTofu modules, automation, and platform tooling.
• Implement and troubleshoot complex AWS and Kubernetes/EKS platform solutions.
• Build self-service capabilities and reusable paved-road patterns for Engineering teams.
• Lead root-cause analysis and drive permanent technical fixes for complex platform issues.
• Contribute implementation expertise and technical recommendations to architecture and design decisions.
• Apply AI-assisted and agentic automation to appropriate engineering use cases.
• Mentor other engineers and lead technical workstreams when required.
• Improve existing frameworks, standards, automation, reliability, and developer experience.

Behavioral Competencies: