Principal Engineer Automation

• 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.

• 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.

• 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.

• 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.

• 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 capabilities across unit component contract integration regression performance resiliency and end-to-end testing.

• Design highly available fault-tolerant scalable systems that can support mission-critical engineering and infrastructure workflows.
• Establish service-level indicators service-level objectives error budgets availability targets capacity expectations and production-readiness requirements for platform services.
• Design observability architectures using metrics logs traces events flow data streaming telemetry and business-level workflow indicators.
• Implement dashboards alerts service health indicators dependency views and diagnostic capabilities using technologies such as OpenTelemetry Prometheus Grafana ELK Splunk and distributed tracing platforms.
• Lead the development of automated detection diagnostics remediation rollback and evidence-capture patterns.
• Apply failure-mode analysis resilience testing controlled fault injection capacity testing and performance engineering to identify risks before production adoption.
• Ensure platform teams receive actionable health information rather than relying solely on infrastructure alerts or manual investigation.

• Design and develop governed AI-assisted engineering services that improve knowledge discovery software development test generation release analysis operational diagnostics evidence summarization and engineering decision support.
• Build AI application capabilities using retrieval-augmented generation semantic search structured outputs tool integration model evaluation and human-in-the-loop approval patterns.
• Develop knowledge services that use approved and authoritative engineering sources including standards documentation software repositories release evidence test results network state telemetry and operational history.
• Establish clear boundaries between AI recommendation and production execution. AI-generated recommendations must remain explainable traceable reviewable and subject to approved policy or human controls.
• Define evaluation methods for source grounding retrieval quality response accuracy unsupported claims recommendation usefulness and operational risk.
• Partner with security data risk legal compliance and AI governance teams to ensure AI-enabled capabilities meet enterprise requirements.

• Embed security resiliency auditability and policy enforcement into software architecture and platform design rather than treating them as post-development activities.
• Design identity authorization secrets management service account certificate data protection and least-privilege patterns for platform services and integrations.
• Establish guardrails that prevent unauthorized execution bypass of required approvals unverified artifact promotion uncontrolled configuration changes or use of untrusted data.
• Ensure platform actions and workflow transitions produce sufficient evidence for troubleshooting compliance risk review and audit.
• Partner with Information Security and Risk organizations to translate policies and standards into enforceable software controls and measurable engineering requirements.
• Identify technical risks proactively and lead the design and implementation of appropriate mitigation strategies.

• Translate leadership vision business priorities and enterprise technology objectives into executable software strategies architectural roadmaps platform capabilities and engineering initiatives.
• Provide vision direction and technical expertise to leadership on major engineering investments modernization opportunities platform decisions and emerging technologies.
• Influence engineering direction across multiple teams and organizations without relying on direct management authority.
• Define reusable architecture patterns and drive consistent implementation across software infrastructure network reliability and automation teams.
• Mentor senior engineers technical leads architects and emerging principal engineers through design collaboration code review technical forums and structured knowledge sharing.
• Maintain knowledge of industry engineering practices software frameworks cloud-native platforms AI technologies observability methods and network automation developments.
• Evaluate new technologies through prototypes and evidence-based assessments then define adoption guidance implementation patterns and production-readiness criteria.
• Promote a culture of engineering ownership automation measurement experimentation documentation and continuous improvement.

• 7 years of Engineering experience or equivalent demonstrated through one or a combination of the following: work experience training military experience education

• 7 years of software engineering platform engineering cloud engineering infrastructure engineering network automation SRE NRE or equivalent experience demonstrated through one or a combination of work experience training military experience or education.
• 5 years of experience designing developing testing and supporting production-grade software distributed systems automation platforms or enterprise integration services.
• 3 plus years of Advanced software development experience using Python and at least one additional modern programming language such as Go Java C# .NET or TypeScript.
• 3 years experience designing and developing APIs microservices asynchronous services event-driven systems workflow services or comparable distributed software components.
• 3 plus years of experience developing software using Git-based workflows pull requests peer review versioning package management CI/CD automated testing and release management.
• 3 plus years of experience deploying or supporting containerized applications using Docker Kubernetes OpenShift or comparable container orchestration platforms.
• 3 plus years of experience integrating multiple systems through REST APIs webhooks messaging events SDKs or service interfaces.
• 3 plus years of experience designing for scalability availability resiliency observability security and operational support.

• Strong knowledge of software engineering fundamentals including data structures algorithms modular design object-oriented or functional design design patterns concurrency error handling automated testing and performance optimization.
• Demonstrated experience leading technical design or architecture across multiple engineering teams platforms or organizational boundaries.
• Strong analytical and systems-thinking skills with the ability to decompose ambiguous enterprise-scale problems into executable engineering solutions.
• Strong written verbal and visual communication skills including the ability to explain complex software and architecture decisions to engineering teams technology leaders and executive stakeholders.
• Prior experience in a Principal Engineer Staff Engineer Senior Staff Engineer Software Architect Platform Architect or comparable technical leadership capacity.
• Demonstrated experience serving as the technical lead for a large-scale software platform and driving architecture and engineering strategy across multiple teams without direct management authority.
• Experience creating reference architectures reusable software frameworks engineering standards or platform services adopted by multiple teams.
• Experience leading architectural reviews software design reviews code-quality initiatives production-readiness reviews or cross-organizational technical programs.
• Demonstrated ability to balance hands-on engineering with strategic influence mentoring governance and long-term technical planning.

• Deep understanding of distributed systems concepts including consistency availability partition tolerance concurrency state management failure recovery idempotency backpressure retries timeouts and compensating transactions.
• Experience designing high-volume highly available or mission-critical services.
• Experience with event-driven architecture message brokers streaming platforms service discovery API gateways caching distributed data systems and asynchronous processing.
• Experience defining versioned APIs service contracts domain models and backward-compatible integration strategies.
• Experience with performance engineering load testing capacity analysis profiling and software optimization.

• Experience building internal developer platforms self-service engineering portals platform-as-a-product capabilities engineering enablement services or reusable delivery frameworks.
• Experience creating paved roads golden paths project templates reusable pipelines service catalogs SDKs or automated onboarding capabilities.
• Experience measuring platform adoption developer productivity delivery lead time reliability support demand or operational toil.
• Experience with developer portals or service catalogs such as Backstage or comparable technologies.

• Hands-on experience with Temporal Celery Argo Workflows Apache Airflow Dagster or another durable workflow or asynchronous execution framework.
• Understanding of workflow activities workers task queues signals queries timers retries workflow versioning replay behavior and durable state.
• Experience designing idempotent fault-tolerant long-running workflows with human approvals and external system dependencies.
• Experience separating orchestration logic from execution logic policy decisions and user-facing intake processes.

• Experience with Docker Kubernetes OpenShift Helm Harness GitHub Actions Azure DevOps Argo CD or comparable build and deployment technologies.
• Experience with Terraform OpenTofu Ansible Pulumi Kubernetes operators or comparable Infrastructure as Code technologies.
• Experience operating software services in Azure AWS Google Cloud private cloud or hybrid-cloud environments.
• Understanding of cloud well-architected practices identity and access management secrets management networking scalability resiliency and cost-conscious engineering.
• Experience with service meshes ingress platforms API management cloud-native networking or policy-as-code technologies.

• Experience developing software for network automation infrastructure automation configuration management software lifecycle management or infrastructure orchestration.
• Knowledge of enterprise networking concepts and technologies including routing switching wireless firewalls load balancing DNS IP address management or network security.
• Experience with network automation interfaces and technologies such as RESTCONF NETCONF gNMI gRPC YANG SNMP streaming telemetry or vendor APIs.
• Experience with Nautobot NetBox or another source-of-truth and network state-management platform.
• Experience with Ansible Nornir pyATS Terraform or comparable infrastructure and network automation frameworks.
• Familiarity with Cisco Juniper Arista Palo Alto Fortinet F5 or comparable enterprise infrastructure platforms.

• Experience implementing observability using OpenTelemetry Prometheus Grafana ELK Splunk distributed tracing structured logging streaming telemetry or flow analytics.
• Experience establishing SLIs SLOs error budgets health indicators alerting standards or production-readiness criteria.
• Familiarity with incident management root-cause analysis automated remediation resilience testing chaos engineering capacity planning and operational toil reduction.
• Experience correlating application behavior infrastructure state network telemetry workflow execution and business outcomes.

• Experience building production AI machine learning generative AI or AI-assisted engineering solutions.
• Experience with retrieval-augmented generation embeddings vector search semantic retrieval knowledge graphs structured model outputs tool calling or prompt orchestration.
• Experience developing AI evaluation frameworks addressing groundedness source coverage retrieval quality unsupported claims classification performance and human acceptance.
• Understanding of responsible AI model governance explainability prompt and model versioning access controls sensitive data protection and human review.
• Experience building data pipelines and working with structured and unstructured data including JSON YAML logs telemetry documents API payloads and software repository content.

• Experience with information security and technology risk management including secure development security architecture threat modeling policy and standards security assessments mitigation design and control implementation.
• Experience incorporating identity authorization least privilege secrets management data protection auditability and policy enforcement into software platforms.
• Financial services experience or experience within another highly regulated industry.

• Bachelors or advanced degree in Computer Science Software Engineering Computer Engineering Information Systems Data Science or a related technical field.
• Relevant certifications such as CCIE CCDE JNCIE Microsoft Azure Solutions Architect Expert AWS Certified Solutions Architect Professional Google Professional Cloud Architect Certified Kubernetes Administrator Certified Kubernetes Application Developer or comparable certifications.

The successful candidate will demonstrate measurable progress in the following areas:

• Adoption of reusable platform services APIs SDKs workflows and engineering patterns across multiple teams.
• Reduction in one-off scripts duplicated automation manual handoffs and operational toil.
• Improvement in software quality through automated testing code review reusable components release controls and consistent engineering standards.
• Increased reliability and transparency through defined service objectives observability resilient architecture controlled failure handling and actionable diagnostics.
• Faster and safer delivery through self-service capabilities standardized CI/CD automated governance reusable workflows and controlled environment promotion.
• Stronger alignment among source-of-truth data software repositories workflow state approval evidence production execution and actual infrastructure state.
• Clear adoption of AI-assisted engineering capabilities without creating an uncontrolled execution or approval path.
• Effective technical influence across engineering architecture operations security risk and leadership organizations.

Posting End Date:

*Job posting may come down early due to volume of applicants.

We Value Equal Opportunity

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