Overview

We are looking for a DevOps Engineer IV - Platform Engineering with deep expertise in cloud and platform architecture, DevOps, Infrastructure as Code, GitOps, Kubernetes, automation, and enterprise platform engineering.

Responsibilities

• Define and evolve Platform Engineering architecture and strategy across AWS and Azure where applicable, ensuring scalability, availability, reliability, security, operability, and cost efficiency
• Define standardized reference architectures, engineering standards, and reusable platform patterns across networking, compute, storage, IAM, Kubernetes, serverless, observability, and application delivery.
• Architect standardized cloud platforms and paved roads that enable Engineering teams to consume infrastructure and platform capabilities through secure self-service mechanisms.
• Lead architecture and design reviews and ensure solutions align with enterprise engineering, security, governance, and operational standards.
• Evaluate emerging cloud-native technologies and establish architectural direction based on technical and business requirements.
• Define architecture and standards for reusable Infrastructure as Code using Terraform/OpenTofu, including modular design, versioning, testing, governance, and lifecycle management.
• Establish IaC patterns that can be consistently adopted across multiple products, environments, and cloud accounts.
• Define automation strategies that reduce manual infrastructure, deployment, and operational activities.
• Establish architecture patterns for integrating infrastructure provisioning with CI/CD and GitOps workflows.
• Define approaches for infrastructure lifecycle management, configuration validation, drift detection, policy enforcement, and automated remediation.
• Guide development of platform automation, APIs, utilities, and integrations using appropriate programming and scripting technologies.
• Define and drive GitOps architecture, standards, and operating models using Argo CD, Flux, or equivalent technologies.
• Establish standards for declarative configuration, repository architecture, environment promotion, automated reconciliation, secrets management, drift detection, rollback, RBAC, and policy enforcement.
• Integrate GitOps practices with Kubernetes, Infrastructure as Code, CI/CD pipelines, security controls, and enterprise governance.
• Define reusable deployment patterns including blue/green, canary, progressive delivery, automated rollback, and policy-driven deployments.
• Guide teams in resolving complex GitOps, CI/CD, and deployment architecture challenges.
• Define architecture and engineering standards for enterprise container platforms, including Amazon EKS and Azure AKS where applicable.
• Establish Kubernetes architecture patterns covering cluster design, networking, workload isolation, identity, security, scalability, observability, storage, and lifecycle management.
• Define reusable patterns for deploying and operating cloud-native applications and shared platform services.
• Evaluate Kubernetes ecosystem technologies and establish standards based on enterprise requirements.
• Provide architectural guidance for complex Kubernetes platform, networking, security, scaling, and reliability challenges
• Architect Internal Developer Platform capabilities that simplify infrastructure provisioning and application delivery for product Engineering teams.
• Define reusable platform services, templates, APIs, workflows, and self-service capabilities.
• Establish golden paths/paved roads that abstract infrastructure complexity while maintaining security, governance, reliability, and operational controls.
• Partner with Engineering teams to understand developer needs and evolve platform capabilities and standards
• Define platform success metrics covering adoption, developer productivity, automation coverage, reliability, deployment efficiency, and reduction of manual effort.
• Define architecture patterns for incorporating AI and agentic capabilities into DevOps and Platform Engineering workflows.
• Identify high-value opportunities for AI across infrastructure automation, CI/CD, troubleshooting, incident analysis, operational support, documentation, and developer self-service.
• Evaluate enterprise AI technologies such as Amazon Bedrock, Azure OpenAI/OpenAI, or equivalent platforms and define secure integration patterns.
• Establish patterns for AI agents to interact securely with cloud services, APIs, engineering platforms, repositories, and operational tooling.

Qualifications

• 10+ years of experience in DevOps, Cloud Engineering, Platform Engineering, Infrastructure Engineering, Software Engineering, or a related role
• Extensive experience designing enterprise-scale cloud and platform architectures.
• Deep expertise in AWS architecture, services, and best practices.
• Expert-level experience with Terraform/OpenTofu, including modular architecture, reusable frameworks, governance, testing, and enterprise-scale implementations.
• Strong experience with Kubernetes and enterprise container platforms, particularly EKS and/or AKS.
• Deep understanding of Kubernetes architecture, networking, security, identity, scaling, observability, storage, and lifecycle management.
• Strong understanding of GitOps architecture and operating models with experience designing solutions using Argo CD, Flux, or equivalent technologies.
• Strong understanding of CI/CD architecture and enterprise software-delivery practices.
• Deep understanding of IAM, RBAC, cloud security, least-privilege architecture, policy-as code, compliance, and audit controls.
• Strong understanding of distributed systems, scalability, high availability, disaster recovery, resiliency, and performance architecture.
• Strong automation and scripting/programming skills using Python, Go, PowerShell, Bash, TypeScript, or equivalent technologies.
• Demonstrated technical and architectural leadership across multiple engineering teams and complex initiatives.
• Ability to translate business and engineering requirements into scalable platform architecture, reference patterns, and technical standards.
• AWS, Terraform, Kubernetes, architecture, or other relevant certifications are a plus.
• Enterprise architecture and systems-thinking mindset
• Strong ability to evaluate architectural trade-offs and establish scalable technical direction.
• Ability to balance standardization, developer experience, security, reliability, and cost.
• Demonstrated technical leadership, mentoring, and influence across engineering teams without requiring formal people-management authority.
• Ability to lead complex cross-team technical initiatives and drive alignment among multiple stakeholders.
• Strong problem-solving and decision-making skills for ambiguous and complex platform challenges.
• Strong written and verbal communication skills with the ability to communicate architecture to engineers, architects, and leadership.
• Continuous-learning mindset and ability to evaluate emerging cloud, platform, and AI technologies.
• Define and evolve enterprise Platform Engineering architecture, reference patterns, and technical standards.
• Architect scalable, secure, resilient, and cost-efficient cloud platform capabilities across AWS and related technologies.
• Define enterprise approaches for Terraform/OpenTofu, GitOps, Kubernetes, CI/CD, automation, governance, observability, and developer self-service.
• Lead architecture and design reviews and guide teams through complex technical trade offs.
• Drive reusable paved roads and Internal Developer Platform capabilities that can be adopted across multiple product teams.
• Define architecture patterns for AI-assisted and agentic Platform Engineering capabilities with appropriate enterprise guardrails
• Provide technical leadership for complex cross-team initiatives from design through operational readiness.
• Mentor engineers and raise engineering and architecture standards across the organization.