Staff Cloud Infrastructure Architect

POSITION SUMMARY

The Staff Cloud Infrastructure Architect shapes resilient, secure, and scalable cloud foundations that accelerate Empower's growth, protect business operations, and improve technology economics. This role owns architecture standards, reference patterns, modernization roadmaps, and technical decisions across Azure, AWS, networking, platform engineering, and Infrastructure-as-Code, partnering with Security, Quality, Data, and Application teams. AI serves as a force multiplier to increase delivery speed, operational scale, engineering quality, and decision-making through intelligent automation, predictive insights, and problem resolution. Success requires navigating Empower's hyper-growth, highly regulated 503A/503B environment with disciplined risk management, audit readiness, and execution. The role demands strategic thinking, execution rigor, learning agility, and leadership to convert ambiguity into infrastructure capabilities that support compliant innovation, reliability, and performance while raising architectural standards and engineering accountability enterprise-wide.

RESPONSIBILITIES

Cloud Strategy and Architecture

• Strategic Architecture: Define cloud architecture principles, target states, and reference patterns across Azure and AWS, translating business priorities into sequenced modernization roadmaps. Apply AI-assisted analysis to compare options, model cost, performance, and risk, and improve decision quality. Own major technical choices, document tradeoffs, and guide teams toward scalable, resilient platforms that support Empower's regulated growth, operational continuity, and rapidly evolving product, data, manufacturing, and customer experience needs across the enterprise.
• Platform Modernization: Architect the migration of on-premises and data center workloads to cloud-native services, balancing speed, compliance, reliability, and total cost. Use AI-enabled discovery, dependency mapping, and workload assessment to accelerate planning and reduce execution risk. Establish repeatable patterns for landing zones, connectivity, identity, compute, storage, and recovery, ensuring modernization efforts produce measurable business outcomes, stronger engineering velocity, and durable foundations for Empower's expanding 503A and 503B operations.
• Capacity Intelligence: Design infrastructure capacity, resilience, and performance strategies that anticipate demand rather than react to incidents. Combine observability data with AI-driven forecasting to identify saturation, optimize resource allocation, and automate scaling decisions. Define service objectives, failure thresholds, and recovery patterns for critical platforms, ensuring business growth is supported without compromising availability, security, or quality. Communicate infrastructure constraints and investment needs clearly to technology and business leaders before material risk emerges.

Engineering Excellence and Automation

• Code Standards: Establish and govern Infrastructure-as-Code standards using Terraform, cloud-native tooling, modular patterns, testing, and policy controls. Integrate AI-assisted code generation, review, documentation, and defect detection to improve speed and quality while preserving human accountability. Create reusable modules and golden paths that reduce variation, strengthen traceability, and enable teams to deploy compliant infrastructure consistently across environments. Measure adoption, exceptions, deployment reliability, and cycle-time improvements, then refine standards based on evidence.
• Operational Automation: Engineer intelligent automation for provisioning, patching, configuration, monitoring, incident response, and routine operational work. Use AI and machine learning to correlate signals, prioritize anomalies, recommend remediation, and reduce mean time to resolution without creating uncontrolled automation risk. Build approval gates, audit trails, rollback mechanisms, and measurable controls so automation improves speed, scale, and service quality. Eliminate recurring toil and redirect engineering capacity toward modernization, reliability, and business-enabling platform capabilities.
• Technical Leadership: Provide hands-on architectural leadership for complex initiatives, reviewing designs, resolving constraints, and raising engineering quality across teams. Mentor engineers through structured feedback, technical forums, and reusable guidance, encouraging responsible use of AI to accelerate learning and problem-solving. Influence without relying on authority, align stakeholders around sound decisions, and maintain execution momentum through ambiguity. Model the learning agility, rigorous follow-through, and ownership expected of high-performing Staff-level technical talent across Empower.

Security, Compliance, and Partnership

• Security Architecture: Embed security, privacy, and compliance requirements into cloud architecture from design through operation. Partner with Cybersecurity and Quality teams to implement identity, segmentation, encryption, logging, vulnerability management, and policy enforcement. Apply AI-enabled threat analytics and configuration assessment to identify exposure earlier while validating outputs against approved controls. Ensure architectures support least privilege, defense in depth, secure recovery, and evidence generation appropriate for Empower's highly regulated 503A and 503B environment.
• Risk Governance: Translate technical risk into clear business impact, mitigation options, ownership, and deadlines. Maintain architecture decisions, control evidence, exceptions, and remediation plans that strengthen audit readiness and executive visibility. Use AI-assisted analysis to surface patterns across incidents, vulnerabilities, cost anomalies, and compliance findings, accelerating prioritization without replacing expert judgment. Lead root-cause reviews and preventive actions that improve resilience, reduce repeat failures, and demonstrate disciplined stewardship of critical infrastructure investments.
• Cross-Functional Partnership: Collaborate with Application, Data, Security, Manufacturing, Quality, Finance, and vendor teams to deliver cloud capabilities that solve business problems rather than isolated technology goals. Use AI-supported synthesis to accelerate requirements analysis, scenario planning, documentation, and stakeholder decisions. Establish clear interfaces, decision rights, and success measures across initiatives. Challenge assumptions constructively, resolve competing priorities, and build trust through transparent tradeoffs, dependable execution, and outcomes aligned with Empower's growth, compliance, and customer commitments.

KNOWLEDGE AND SKILLS

• Expert knowledge of Azure and AWS architecture, networking, identity, resilience, observability, and cloud economics, with the judgment to select practical patterns for regulated, high-growth environments.
• Advanced proficiency with Terraform, Infrastructure-as-Code lifecycle practices, CI/CD, policy-as-code, automated testing, and AI-assisted engineering workflows that improve deployment speed, consistency, and traceability.
• Strong command of cloud security, risk management, disaster recovery, audit evidence, and compliance-by-design principles, including the ability to translate control requirements into scalable technical architecture.
• Exceptional systems thinking, communication, and influence skills, with the learning agility and execution rigor to lead complex decisions, mentor engineers, and align technical work with business outcomes.

EXPERIENCE AND QUALIFICATIONS

• Bachelor's degree in Computer Science, Engineering, Information Systems, or a related field, or an equivalent combination of advanced technical education and relevant experience.
• Ten (10) or more years of progressive infrastructure or cloud engineering experience, including substantial architecture ownership across Azure, AWS, enterprise networking, platform services, and large-scale modernization programs.
• Demonstrated success designing and implementing secure, resilient, and automated cloud platforms in fast-paced environments with strong governance, availability, auditability, and cost-management expectations.
• Proven experience with Terraform, cloud landing zones, identity and access management, observability, disaster recovery, CI/CD, and responsible application of AI within engineering and operations workflows.

CERTIFICATIONS

• Azure Solutions Architect Expert and Terraform certification strongly preferred.
• Azure Administrator, Azure AI Engineer, Kubernetes, AWS Solutions Architect, or ITIL credentials preferred.