Principal Engineer - AWS Cloud Security

Wells Fargo•Columbus, OH

3d•$159,000 - $254,000•Onsite

About The Position

Wells Fargo is seeking a Principal Engineer in Cybersecurity as part of Identity Access Management Engineering. This role will serve as the technical leader responsible for helping define, design, build, and secure the firm's AWS cloud capabilities at enterprise scale. The successful candidate will establish the security architecture, engineering standards, guardrails, automation frameworks, and operating model required to enable secure adoption of AWS across the company. This individual will work across Cyber Security, Infrastructure Engineering, Identity & Access Management, Data Protection, Risk Management, and Application Development teams to build a modern cloud platform that aligns with the firm's security, resilience, regulatory, and operational objectives.

Requirements

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 information security, infrastructure, or cloud engineering experience
5+ years designing and securing AWS environments

Nice To Haves

Experience leading large-scale enterprise cloud transformation initiatives
Experience designing security controls for highly regulated environments
Demonstrated success influencing technical strategy across large organizations
Experience integrating cloud platforms with enterprise IAM, PAM, and cybersecurity ecosystems
Experience supporting multi-cloud environments
Advanced AWS expertise across identity management, networking, encryption, logging, threat detection, and cloud governance
Experience securing containerized and cloud-native workloads using Kubernetes, EKS, ECS, and serverless technologies
Strong proficiency with Infrastructure as Code (Terraform, CloudFormation) and automated cloud provisioning
Deep understanding of Zero Trust architecture, DevSecOps, CI/CD security, and software supply chain security
Experience implementing cloud security controls, policy enforcement, governance frameworks, and security automation at scale
Ability to communicate with engineers, executives, auditors, and regulators
Exceptional architecture and design documentation skills
Proven ability to drive consensus across diverse stakeholder groups
Relevant cloud and security certifications preferred, such as AWS Solutions Architect Professional, AWS Security Specialty, CISSP, CCSP, Certified Kubernetes Security Specialist (CKS), or equivalent credentials.

Responsibilities

Act as an advisor to leadership to develop or influence applications, network, information security, database, operating systems, or web technologies for highly complex business and technical needs across multiple groups
Lead the strategy and resolution of highly complex and unique challenges requiring in-depth evaluation across multiple areas or the enterprise, delivering solutions that are long-term, large-scale and require vision, creativity, innovation, advanced analytical and inductive thinking
Translate advanced technology experience, an in-depth knowledge of the organizations tactical and strategic business objectives, the enterprise technological environment, the organization structure, and strategic technological opportunities and requirements into technical engineering solutions
Provide vision, direction and expertise to leadership on implementing innovative and significant business solutions
Maintain knowledge of industry best practices and new technologies and recommends innovations that enhance operations or provide a competitive advantage to the organization
Strategically engage with all levels of professionals and managers across the enterprise and serve as an expert advisor to leadership
Demonstrate proficiency in using AI‑assisted development and analysis tools (e.g., GitHub Copilot and approved code‑centric agents)
Leverage AI to accelerate system design, coding, testing, analysis, and troubleshooting
Apply strong technical judgment when validating and integrating AI‑assisted outputs into solutions
Understand and account for model limitations, security risks, and operational considerations
Apply AI responsibly in development and production environments
Ensure AI usage aligns with security, compliance, privacy, and ethical standards