Cybersecurity AI Principal Engineer

Wells Fargo

. Design and evolve VoltAIre, a secure, highly available, scalable, isolated, and resilient Cyber AI platform .

Posted 11/6/2026full-timeUnited StatesLead💰 $159,000 - $305,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates extensive experience in designing and implementing scalable, resilient Cyber AI platforms, with a strong focus on cloud architectures, Kubernetes, and distributed systems. Proven ability to lead technical teams, mentor engineers, and drive architectural decisions while ensuring compliance with security and ethical standards.

Highest-signal resume keywords

Cloud Architecture ExperienceKubernetes Application DesignDistributed Systems ArchitectureCybersecurity Platform ExpertiseAI-Assisted Development Proficiency

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Rust ProgrammingGo ProgrammingPython ProgrammingJava ProgrammingSQL TechnologiesNoSQL TechnologiesPerformance EngineeringCapacity ManagementDisaster Recovery DesignObservability Practices

Soft Skills

Strategic ThinkingAnalytical Problem-SolvingMentoring AbilityOrganizational SavvyCustomer Centricity

Tools & Technologies

Google Cloud PlatformMicrosoft AzureAWSGitHub CopilotAI/ML PlatformsLogging and Monitoring ToolsTelemetry ToolsDistributed Application Design ToolsContainer Orchestration PlatformsSecurity Scanners

Industry Keywords

Cyber AIGenerative AIAgentic AIFinancial ServicesRegulated Industry Experience

Tech Stack

Tools & technologies

AWSAzureCloudCyber SecurityDistributed SystemsGoogle Cloud PlatformJavaKubernetesNoSQLPythonRustSQLGo

About the role

Key responsibilities & impact

Design and evolve VoltAIre, a secure, highly available, scalable, isolated, and resilient Cyber AI platform
Advise leadership and influence architecture across applications, cloud infrastructure, networking, information security, data platforms, Kubernetes, and distributed systems
Provide technical leadership for reusable platform capabilities and architectural patterns across cloud and on-premises environments
Design and influence Cyber AI applications including vulnerability scanners, knowledge assistants, security services, and AI-enabled applications
Evaluate workload characteristics and make fit-for-purpose architecture decisions across security, isolation, availability, scalability, resiliency, performance, operational complexity, and cost
Define deployment and isolation patterns across shared Kubernetes clusters, dedicated clusters, regions, infrastructure, and cloud providers
Design highly available and resilient architectures with elastic scaling, active/active, active/passive, and disaster recovery patterns
Provide architectural direction across Kubernetes, load balancing, application networking, compute, storage, SQL and NoSQL technologies, observability, and distributed application design
Re-engineer critical software components requiring deeper systems-level engineering
Establish platform capabilities for logging, monitoring, telemetry, observability, security, adaptive runtime optimization, and intelligent workload routing
Lead resolution of complex technical challenges across applications, infrastructure, cloud, cybersecurity, and enterprise technology
Translate technology experience and business requirements into scalable engineering solutions and articulate architectural trade-offs
Drive solutions from architecture and prototyping through implementation, production deployment, troubleshooting, and continuous optimization
Track emerging technologies across cloud-native platforms, distributed systems, cybersecurity, Generative AI, Agentic AI, and systems engineering
Engage with engineers, architects, product teams, cybersecurity partners, and leadership as an expert technical advisor
Mentor senior and staff engineers and establish reusable engineering patterns
Leverage AI to accelerate system design, coding, testing, analysis, and troubleshooting
Validate and integrate AI-assisted outputs while ensuring alignment with security, compliance, privacy, and ethical standards

Requirements

What you’ll need

7+ years of Engineering experience, or equivalent demonstrated through work experience, training, military experience, or education
7+ years of senior engineering experience, including architecture and hands-on delivery of large-scale platforms, distributed applications, and production systems
3+ years of hands-on experience with cloud architectures, including Google Cloud Platform, Microsoft Azure, AWS, or comparable enterprise cloud technologies
Experience designing, building, and operating applications and services on Kubernetes or comparable container orchestration platforms
Experience with distributed systems and application architecture, including networking, load balancing, APIs, data flows, concurrency, persistence, scalability, and failure handling
Experience designing solutions using SQL and/or NoSQL data technologies
Experience designing highly available and resilient production systems, including scaling, redundancy, failure recovery, and disaster recovery
Ability to work at both hands-on technical depth and strategic architecture level
Experience designing platforms supporting multiple workloads or tenants with differing security, isolation, availability, scalability, performance, and resiliency requirements
Experience with hybrid or multi-cloud architectures spanning public cloud and on-premises infrastructure
Strong software engineering background in Rust, Go, Python, Java, or comparable languages; systems programming experience particularly valuable
Experience with large-scale Kubernetes platforms, distributed workloads, and cloud-native applications through production
Experience with observability platforms and practices, including logging, metrics, monitoring, telemetry, tracing, and production troubleshooting
Experience with active/active, active/passive, regional redundancy, disaster recovery, and other high-availability patterns
Experience with performance engineering, capacity management, elastic scaling, and runtime optimization
Experience working within agile product operating models in large enterprise environments
Ability to mentor senior and staff engineers
Strategic thinking, analytical problem-solving, and sound technical judgment
Curiosity and innovation mindset for Generative AI, Agentic AI, and Cyber AI capabilities
Experience with cybersecurity platforms, vulnerability management, SAST, DAST, security scanners, AI/ML platforms, or compute-intensive distributed workloads
Strong organizational savvy and customer centricity
Financial services or other highly regulated industry experience is beneficial
Demonstrate proficiency in AI-assisted development and analysis tools, such as GitHub Copilot and approved code-centric agents
Ability to apply AI responsibly and account for model limitations, security risks, operational considerations, security, compliance, privacy, and ethical standards
Position is not eligible for Visa sponsorship

Benefits

Comp & perks

Health benefits
401(k) Plan
Paid time off
Disability benefits
Life insurance, critical illness insurance, and accident insurance
Parental leave
Critical caregiving leave
Discounts and savings
Commuter benefits
Tuition reimbursement
Scholarships for dependent children
Adoption reimbursement
Incentive opportunities may be available