DevOps Engineer IV

Job Responsibilities:

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.

Required Skills & Experience:

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.

Preferred Skills :

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.

Key Competencies:

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.

Behavioral Competencies:

Cultivates Innovation

Decision Quality

Manages Complexity

Drives Results

Business Insight