Principal Architect Automation

Wells Fargo & Company•Irving, TX

About The Position

The Principal Architect Automation serves as a trusted technical advisor to senior leadership and shapes architecture and development across applications, platforms, APIs, network automation services, information security capabilities, data systems, operating environments, and cloud-native technologies. The role leads resolution of complex engineering challenges and delivers secure, resilient, maintainable, large-scale solutions. It combines hands-on software and platform engineering with enterprise technical strategy and influence across multiple teams and organizations. The architect designs production-grade platforms, APIs, microservices, SDKs, libraries, automation frameworks, and distributed, event-driven systems. The role establishes engineering standards, builds reusable internal engineering platforms and developer experiences, and designs durable workflows for long-running infrastructure and network processes. It also defines integration and data architectures, cloud-native deployment and CI/CD practices, reliability and observability approaches, governed AI-assisted engineering capabilities, and security and risk controls. The successful candidate translates business priorities and leadership vision into architectural roadmaps and platform capabilities; influences engineering direction without relying on direct management authority; mentors technical leaders and engineers; evaluates emerging technologies; and promotes engineering ownership, automation, measurement, documentation, and continuous improvement. Success is measured by adoption of reusable platform capabilities, reduced duplication and operational toil, improved software quality and reliability, faster and safer delivery, stronger alignment of data and production state, responsible adoption of AI-assisted engineering, and effective technical influence across the organization.

Requirements

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

Nice To Haves

Strong knowledge of software engineering fundamentals, including data structures, algorithms, modular design, object-oriented or functional design, design patterns, concurrency, error handling, testing, and performance optimization.
Experience leading technical design or architecture across multiple engineering teams, platforms, or organizational boundaries.
Strong analytical and systems-thinking skills to turn ambiguous, enterprise-scale problems into executable engineering solutions.
Strong written, verbal, and visual communication skills, including explaining complex architecture decisions to engineering teams, technology leaders, and executives.
Prior experience as a Principal Engineer, Staff Engineer, Senior Staff Engineer, Software Architect, Platform Architect, or in a comparable technical leadership capacity.
Experience serving as technical lead for a large-scale software platform and driving architecture and engineering strategy across teams without direct management authority.
Experience creating reference architectures, reusable software frameworks, engineering standards, or platform services adopted by multiple teams.
Experience leading architecture, software design, code-quality, production-readiness reviews, or cross-organizational technical programs.
Ability to balance hands-on engineering with strategic influence, mentoring, governance, and long-term technical planning.
Deep understanding of distributed systems, 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; event-driven architectures; 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; performance engineering, load testing, capacity analysis, profiling, and optimization.
Experience building internal developer platforms, self-service engineering portals, platform-as-a-product capabilities, enablement services, or reusable delivery frameworks.
Experience creating paved roads, golden paths, project templates, reusable pipelines, service catalogs, SDKs, or automated onboarding; measuring adoption, 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, versioning, replay behavior, and durable state; experience designing idempotent, fault-tolerant, long-running workflows with human approvals and external 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 services in Azure, AWS, Google Cloud, private cloud, or hybrid-cloud environments; understanding of cloud architecture, IAM, secrets, 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 such as routing, switching, wireless, firewalls, load balancing, DNS, IP address management, or network security.
Experience with RESTCONF, NETCONF, gNMI, gRPC, YANG, SNMP, streaming telemetry, or vendor APIs; Nautobot, NetBox, or another source-of-truth platform; Ansible, Nornir, pyATS, Terraform, or comparable 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 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; with retrieval-augmented generation, embeddings, vector search, semantic retrieval, knowledge graphs, structured outputs, tool calling, or prompt orchestration.
Experience developing AI evaluation frameworks for 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, policies 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 in another highly regulated industry.
Bachelor’s 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.

Responsibilities

Advise senior leadership and influence architecture and development across applications, platforms, APIs, network automation, security, data systems, operating environments, and cloud-native technologies.
Lead the strategy and resolution of complex engineering challenges, delivering secure, resilient, maintainable, large-scale solutions.
Design, develop, and contribute to production-grade software platforms, APIs, microservices, SDKs, libraries, automation frameworks, and reusable components.
Define architectures for distributed, event-driven, asynchronous systems, including service boundaries, contracts, workflow state, integration patterns, failure handling, concurrency, consistency, and recovery.
Establish engineering standards for application structure, API design, code quality, testing, secure development, dependencies, versioning, release engineering, observability, and production readiness.
Develop reference implementations and contribute hands-on to technically complex platform capabilities.
Lead technical design, architecture, code, failure-mode, and production-readiness reviews.
Build and evolve internal engineering platforms that provide self-service automation, standardized workflows, reusable services, governed execution, and consistent developer experiences.
Manage shared engineering platforms as products, defining users, service contracts, roadmaps, adoption measures, documentation, support models, and reliability objectives.
Create paved roads and golden paths, and improve developer productivity through reusable APIs, templates, SDKs, CI/CD pipelines, test harnesses, development environments, documentation, and onboarding.
Reduce duplicated engineering effort and operational toil by creating reusable platform services, libraries, automation modules, and supported integration patterns.
Establish 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 workflow and asynchronous execution technologies.
Define workflow patterns for activities, workers, task queues, events, signals, timers, retries, timeouts, compensating actions, versioning, idempotency, replay safety, and human approval gates.
Build workflows that preserve state across failures, support controlled resumption, provide execution history, and align validation, business approval, and production execution.
Create reusable workflow components for intake, validation, certification, approvals, change alignment, deployment, verification, rollback, evidence collection, exception handling, and closeout.
Define 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 support independent evolution while maintaining compatibility, security, and traceability.
Build integrations using REST, RESTCONF, NETCONF, gRPC, webhooks, message queues, event streams, OpenAPI, and structured data formats.
Develop data pipelines and services to collect, validate, normalize, correlate, and expose network state, software lifecycle data, workflow data, telemetry, release evidence, and operational outcomes.
Establish data quality, lineage, ownership, freshness, access, retention, reconciliation, and authoritative-source patterns.
Integrate network source-of-truth platforms such as Nautobot or NetBox with automation, workflows, intended-state models, telemetry, compliance checks, and drift detection.
Design, build, and operate containerized services using Docker, Kubernetes, OpenShift, Helm, or comparable technologies.
Develop CI/CD and GitOps capabilities for build, testing, security validation, policy enforcement, artifact promotion, deployment, and release verification.
Establish safe software and configuration promotion patterns across development, test, UAT, and production.
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 unit, component, contract, integration, regression, performance, resiliency, and end-to-end testing capabilities.
Design highly available, fault-tolerant, scalable systems for mission-critical engineering and infrastructure workflows.
Establish service-level indicators, objectives, error budgets, availability targets, capacity expectations, and production-readiness requirements.
Design observability architectures using metrics, logs, traces, events, flow data, streaming telemetry, and workflow indicators; implement dashboards, alerts, health indicators, dependency views, and diagnostics.
Lead development of automated detection, diagnostics, remediation, rollback, and evidence-capture patterns.
Apply failure-mode analysis, resilience testing, fault injection, capacity testing, and performance engineering to identify production risks.
Provide platform teams with actionable health information rather than relying solely on infrastructure alerts or manual investigation.
Design governed AI-assisted engineering services for knowledge discovery, development, test generation, release analysis, operational diagnostics, evidence summarization, and decision support.
Build AI application capabilities using retrieval-augmented generation, semantic search, structured outputs, tool integration, model evaluation, and human-in-the-loop approvals.
Develop knowledge services using approved and authoritative engineering sources.
Keep AI recommendations explainable, traceable, reviewable, and subject to approved policies or human controls; define evaluation methods for grounding, retrieval quality, accuracy, unsupported claims, usefulness, and risk.
Partner with security, data, risk, legal, compliance, and AI governance teams on enterprise requirements for AI capabilities.
Embed security, resiliency, auditability, and policy enforcement into architecture and platform design.
Design identity, authorization, secrets, service account, certificate, data protection, and least-privilege patterns.
Establish guardrails against unauthorized execution, bypassed approvals, unverified artifact promotion, uncontrolled configuration changes, and untrusted data.
Ensure platform actions and workflow transitions produce evidence for troubleshooting, compliance, risk review, and audit.
Partner with Information Security and Risk organizations to translate policies and standards into enforceable controls and measurable engineering requirements.
Identify technical risks proactively and lead mitigation design and implementation.
Translate leadership vision, business priorities, and enterprise objectives into software strategies, architectural roadmaps, platform capabilities, and engineering initiatives.
Provide technical direction on engineering investments, modernization, platform decisions, and emerging technologies.
Influence engineering direction across teams and organizations without direct management authority; define reusable architecture patterns and drive consistent implementation.
Mentor senior engineers, technical leads, architects, and emerging principal engineers through collaboration, reviews, forums, and knowledge sharing.
Maintain knowledge of engineering practices, software frameworks, cloud-native platforms, AI, observability, and network automation; evaluate technologies and define adoption and production-readiness guidance.
Promote engineering ownership, automation, measurement, experimentation, documentation, and continuous improvement.