DevOps Engineer IV

Platform & Cloud Architecture:

• 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.

Infrastructure as Code & Automation:

• 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.

GitOps & Continuous Delivery:

• 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.

Kubernetes & Cloud-Native Platforms:

• 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.

Platform & Developer Enablement:

• 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.

AI & Agentic Engineering:

• 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.

• Define identity, authorization, observability, governance, cost controls, guardrails, and human-in-the-loop mechanisms for AI-enabled automation.

• Guide reference implementations and proofs of concept to validate AI-enabled platform capabilities before broader adoption.

Security, Governance, FinOps & Reliability:

• Define cloud governance frameworks covering IAM, RBAC, security, compliance, policy as-code, tagging, and cost controls.

• Establish architectural guardrails that enable teams to operate independently while maintaining enterprise security and compliance requirements.

• Define architecture patterns for high availability, disaster recovery, scalability, resiliency, performance, and operational excellence.

• Ensure observability, including monitoring, logging, metrics, tracing, and alerting, is incorporated into platform architecture by design.

• Drive cloud cost optimization architecture and FinOps practices including visibility, allocation, budgeting, forecasting, and optimization.

• Define repeatable architecture and automation patterns supporting cloud migration and modernization initiatives.

Technical Leadership:

• Provide technical leadership and architectural direction for complex Platform Engineering and DevOps initiatives.

• Lead cross-team technical initiatives from architecture and design through implementation and operational readiness.

• Mentor engineers and help develop cloud, DevOps, GitOps, automation, Kubernetes, and architecture capabilities.

• Facilitate architecture and design discussions and guide teams through complex technical trade-offs.

• Influence engineering standards and technical decisions across teams and product areas.

• Coordinate technical efforts across engineering teams when required while continuing to operate as a senior individual contributor.

• Collaborate with Engineering leadership, Product Enablement, SRE, Security, Architecture, and product Engineering teams to align platform strategy with organizational objectives.
• 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.

• Experience with observability, SRE, reliability, operational excellence, and cloud cost/FinOps practices.

• 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.
• Experience designing Internal Developer Platforms and enterprise developer self-service capabilities.

• Experience establishing enterprise paved roads/golden paths across multiple product teams.

• Experience implementing GitOps at scale across multiple Kubernetes clusters, environments, and teams.

• Experience with large-scale cloud migration and modernization programs.

• Experience implementing enterprise cloud governance across multi-account AWS environments.

• Experience with Azure/AKS or other multi-cloud environments.

• Experience designing AI-assisted or agentic DevOps and Platform Engineering workflows using Amazon Bedrock, Azure OpenAI/OpenAI, or equivalent technologies.

• Experience with platform engineering metrics, developer experience, and engineering productivity measurement.

• 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.

Level IV Expectations A DevOps Engineer IV - Platform Engineering should be able to:

• 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.

• Validate architecture through reference implementations, proofs of concept, and sufficient hands-on technical depth.

• Influence technical direction at an organizational level while operating as a senior individual contributor rather than a formal people manager.
• Cultivates Innovation

• Decision Quality

• Manages Complexity

• Drives Results

• Business Insight