Principal Engineer Automation

Аналитика рынка

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Описание

In This Role, You Will Software Architecture and Engineering Act as a trusted technical advisor to senior leadership, influencing the architecture and development of applications, platforms, APIs, network automation services, information security capabilities, data systems, operating environments, and cloud-native technologies for highly complex business and technical needs across multiple organizations. Lead the strategy and resolution of highly complex and unique engineering challenges requiring evaluation across multiple technology domains, delivering solutions that are long-term, large-scale, secure, resilient, and maintainable. Design and develop production-grade software platforms, APIs, microservices, SDKs, libraries, automation frameworks, and reusable components that enable network and infrastructure engineering capabilities across the enterprise. Define software architectures for distributed, event-driven, and asynchronous systems, including service boundaries, data contracts, workflow states, integration patterns, failure handling, concurrency, consistency, and recovery models. Establish software engineering standards for application structure, API design, code quality, automated testing, secure development, dependency management, versioning, release engineering, observability, and production readiness. Develop reference implementations and contribute directly to high-value or technically complex portions of the platform, particularly where new patterns, technologies, or engineering standards must be proven. Lead technical design reviews, architecture reviews, code reviews, failure-mode analysis, and production-readiness assessments for critical platform capabilities. Platform Engineering and Developer Experience Build and evolve internal engineering platforms that provide self-service automation, standardized workflows, reusable services, governed execution paths, and consistent developer experiences. Treat shared engineering platforms as products, with clearly defined users, service contracts, roadmaps, adoption measures, documentation, support models, and reliability objectives. Create paved roads and golden paths that enable engineering teams to develop, test, certify, release, and operate automation through approved patterns rather than one-off implementations. Improve developer productivity through reusable APIs, templates, software development kits, CI/CD pipelines, test harnesses, local development environments, documentation, and automated onboarding. Reduce duplicated engineering effort and operational toil by converting common functions into reusable platform services, shared libraries, automation modules, and supported integration patterns. Establish appropriate boundaries among platform ownership, application ownership, production execution, operational support, and risk decision-making. Workflow Orchestration and Automation Design durable workflows for long-running, failure-prone, approval-dependent infrastructure and network processes using Temporal, Celery, or comparable workflow and asynchronous execution technologies. Define patterns for workflows, activities, workers, task queues, events, signals, timers, retries, timeouts, compensating actions, versioning, idempotency, replay safety, and human approval gates. Build workflow capabilities that preserve state across failures, support controlled resumption, provide complete execution history, and maintain alignment among technical validation, business approval, and production execution. Create reusable workflow components for intake, validation, certification, release approval, change alignment, deployment, verification, rollback, evidence collection, exception handling, and closeout. Define clear execution boundaries among orchestration services, CI/CD platforms, approval systems, source-of-truth platforms, AI advisory services, and automation execution engines. API, Integration, and Data Engineering Design and implement RESTful, event-driven, streaming, and standards-based integrations among enterprise platforms, network infrastructure, source-of-truth systems, workflow engines, observability services, artifact repositories, and change-management systems. Define stable, versioned service contracts and data models that allow platform components to evolve independently while maintaining compatibility, security, and traceability. Build integrations using technologies and protocols such as REST, RESTCONF, NETCONF, gRPC, webhooks, message queues, event streams, OpenAPI specifications, and structured data formats. Develop data pipelines and services that collect, validate, normalize, correlate, and expose network state, software lifecycle data, workflow execution data, telemetry, release evidence, and operational outcomes. Establish patterns for data quality, lineage, ownership, freshness, access control, retention, reconciliation, and authoritative-source designation. Integrate network source-of-truth platforms such as Nautobot or NetBox with automation services, workflow orchestration, intended-state models, actual-state telemetry, compliance checks, and drift-detection processes. Cloud-Native Engineering and CI/CD Design, build, and operate containerized services using Docker, Kubernetes, OpenShift, Helm, and comparable cloud-native technologies. Develop CI/CD and GitOps capabilities that automate build, testing, security validation, policy enforcement, artifact promotion, environment deployment, and release verification. Establish engineering patterns for promoting software and configuration safely across development, test, UAT, and production environments. Implement Infrastructure as Code and configuration automation using technologies such as Terraform, OpenTofu, Ansible, Helm, and Kubernetes manifests. Define standards for source control, branching, pull requests, protected branches, release tags, artifact integrity, dependency controls, and environment-specific configuration. Build automated test capabiliti

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