Platform Engineer, Cloud AI Infrastructure, Sr

OnPoint Credit Union•Portland, OR

About The Position

The Senior Platform Engineer, Cloud & AI Infrastructure designs, builds, automates, and operates secure cloud platforms that enable OnPoint’s AI, data, analytics, and automation capabilities in Azure and Microsoft 365. This is a senior, hands-on engineering role that translates complex requirements into reliable, reusable, production-ready platform services. It provides technical leadership for assigned Azure and AI infrastructure capabilities, including architecture, infrastructure automation, identity and networking integration, observability, resiliency, and cost optimization. The role establishes engineering patterns that help teams move from experimentation to production while maintaining security, supportability, and enterprise standards. Working with Technology Operations, Architecture, Information Security, Data, Solution Engineering, and the Innovation Center of Excellence, the engineer resolves complex platform challenges, mentors engineers, and enables approved self-service capabilities. The position leads through technical expertise and cross-team influence rather than people management. During the first 12 months, expected outcomes include reusable automated deployment patterns; reduced provisioning lead time and manual configuration; production-readiness standards for security, monitoring, support ownership, recovery, and cost; improved reliability and operational visibility; platform cost and capacity baselines with prioritized optimization; and safe experimentation with repeatable promotion into production. The engineer independently leads complex Azure infrastructure design and implementation, develops reference architectures and reusable deployment patterns, and translates business and workload needs into designs balancing reliability, security, performance, cost, and operational complexity. The role engineers infrastructure as code and CI/CD pipelines, supports AI and data platform foundations, implements security and governance controls, defines service-level indicators and objectives, maintains operational documentation and recovery evidence, and leads technical delivery across teams. It also evaluates emerging capabilities, especially in the Microsoft ecosystem, and recommends adoption based on business value, security, maintainability, and total cost. A bachelor’s degree in computer science, information technology, engineering, or a related field—or equivalent professional experience—is required. Candidates must have seven or more years of progressively responsible infrastructure, systems, cloud, or platform engineering experience, including substantial hands-on Azure engineering. An active Microsoft Certified: Azure Solutions Architect Expert certification is required, or the ability to obtain it within 12 months of hire with demonstrated equivalent architecture and engineering experience. The Microsoft Certified: DevOps Engineer Expert certification is preferred.

Requirements

Bachelor’s degree in computer science, information technology, engineering, or a related field, or equivalent professional experience.
Seven or more years of progressively responsible infrastructure, systems, cloud, or platform engineering experience, including substantial hands-on Azure engineering experience.
Demonstrated ability to independently design, implement, and operate complex production cloud solutions.
Advanced knowledge of Azure networking, private connectivity, DNS, identity, role-based access, managed identities, secrets management, and cloud governance.
Demonstrated experience building reusable infrastructure as code and automated deployment pipelines using Git-based engineering practices.
Strong scripting and automation capability using PowerShell, Python, and/or Azure CLI.
Experience implementing observability, performance tuning, capacity management, high availability, and tested disaster recovery.
Hands-on experience supporting production AI or data platform infrastructure, with the ability to explain its security, connectivity, scaling, and operational requirements.
Demonstrated ability to troubleshoot complex, cross-platform issues and lead corrective action.
Experience leading technical implementations, mentoring engineers, and communicating architectural trade-offs.
Active Microsoft Certified: Azure Solutions Architect Expert certification, or ability to obtain it within 12 months of hire, supported by demonstrated equivalent architecture and engineering experience.

Nice To Haves

Microsoft Certified: DevOps Engineer Expert, particularly for candidates with strong infrastructure automation and delivery-pipeline responsibilities.
Experience with Azure-hosted AI services, agent infrastructure, retrieval architectures, and secure model-service connectivity.
Experience with Databricks infrastructure, workspace deployment, private networking, identity integration, and platform monitoring.
Experience with Microsoft Entra ID, Azure Policy, Azure Monitor, Log Analytics, Key Vault, and Microsoft Defender for Cloud.
Experience supporting Microsoft 365, Copilot, or Power Platform integrations and environment governance.
Experience in financial services or another regulated enterprise environment.
Experience developing shared platform services, self-service engineering capabilities, and cloud cost-management practices.

Responsibilities

Independently lead the design and implementation of complex Azure infrastructure spanning compute, storage, networking, identity, security, and shared platform services.
Develop and maintain reference architectures, reusable deployment patterns, and documented technical decisions aligned with enterprise architecture standards.
Translate business and workload requirements into designs that balance reliability, security, performance, cost, and operational complexity.
Identify platform dependencies and constraints, recommend improvements, and contribute to platform roadmaps and lifecycle planning.
Engineer version-controlled infrastructure using Terraform and/or Bicep, supported by PowerShell, Azure CLI, or Python.
Use Microsoft 365 and other platforms to automate corporate functions for IT Operations and advise other teams on automation.
Build and maintain CI/CD pipelines with automated validation, controlled promotion, secure configuration, and recovery or rollback procedures.
Establish reusable modules and approved self-service provisioning patterns that reduce manual work and configuration drift.
Apply code review, testing, documentation, and change-management practices to infrastructure engineering.
Engineer infrastructure foundations for AI services, agent workloads, Databricks, and related enterprise data and automation platforms.
Implement secure connectivity, workload identities, secrets management, environment separation, capacity controls, and platform telemetry.
Partner with application, AI, and data engineers to establish scalable deployment and operational patterns for inference, retrieval, and agent workloads.
Support infrastructure dependencies and integrations for Microsoft 365, Copilot, and Power Platform in partnership with their platform owners.
Define infrastructure ownership, application responsibilities, and support boundaries before production release.
Implement approved identity, access, networking, encryption, policy, and monitoring controls in partnership with Information Security.
Define and monitor service-level indicators and objectives for assigned platform services.
Maintain operational runbooks, configuration evidence, recovery-test results, and technical documentation supporting audit and operational readiness.
Lead technical delivery for complex platform initiatives and coordinate dependencies across teams.
Mentor engineers through design reviews, code reviews, troubleshooting, and knowledge sharing.
Explain technical options, risks, and trade-offs clearly to technical and nontechnical stakeholders.
Evaluate emerging capabilities and recommend adoption based on business value, security, maintainability, and total cost, particularly within the Microsoft ecosystem.
Establish platform cost and capacity baselines and deliver prioritized optimization improvements.
Improve reliability and operational visibility through service health measures, actionable alerts, and tested recovery procedures.
Enable safe experimentation and repeatable promotion into production through approved environments and controls.