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.