Lead Saviynt Engineer

Wells Fargo & Company•Columbus, OH

1d•$119,000 - $187,000•Onsite

About The Position

Wells Fargo is seeking a Lead Software Engineer in Cybersecurity to support its enterprise Identity Governance & Administration (IGA) modernization program. The role focuses on implementing and expanding Saviynt Enterprise Identity Cloud, migrating applications from legacy identity governance platforms, and delivering scalable access governance solutions across the enterprise. The Lead Saviynt Engineer will work with Cybersecurity, application teams, Risk, Product organizations, engineering teams, architects, and professional services partners to onboard applications and deliver platform modernization initiatives. The position provides technical leadership and mentorship across the IGA ecosystem, while applying engineering best practices and responsible use of AI-assisted development tools. The position is based at one of the listed Wells Fargo locations in Charlotte, North Carolina; Irving, Texas; or Columbus, Ohio. It is not available for 100% remote work, and relocation assistance and visa sponsorship are not available. The listed base pay range is $119,000 to $187,000, with potential eligibility for discretionary bonuses, Restricted Share Rights, or other long-term incentive awards.

Requirements

At least 5 years of software engineering experience, or equivalent demonstrated through work experience, training, military experience, education, or a combination of these.
At least 5 years of Identity and Access Management (IAM) experience.
At least 2 years of Saviynt implementation, engineering, or application onboarding experience.
Demonstrated proficiency using AI-assisted development and analysis tools, such as GitHub Copilot and approved code-centric agents.

Nice To Haves

Experience migrating from legacy IGA platforms such as ISIM, SailPoint, or other governance solutions.
Experience with ServiceNow and CyberArk integrations.
Experience supporting SOX, NIST, GDPR, or other regulatory requirements.
Experience delivering proofs of concept, custom workflows, and complex identity governance use cases.
Strong stakeholder management and technical leadership skills.
Experience with application onboarding, access reviews, certifications, entitlement management, and identity lifecycle governance.
Experience integrating enterprise applications using REST APIs, JSON, SQL, and related technologies.
Experience supporting identity governance initiatives in large enterprise environments.
Experience gathering requirements and translating business processes into technical solutions.
Experience in large-scale regulated environments.
Saviynt certification.

Responsibilities

Lead migration of applications and identity governance capabilities from legacy IGA platforms into Saviynt.
Partner with Cybersecurity, application teams, Risk, and Product organizations to onboard on-premises, cloud, and SaaS applications into Saviynt.
Configure and customize Saviynt capabilities, including access reviews, certifications, entitlement management, request workflows, and identity lifecycle processes.
Design and implement proofs of concept and custom solutions for complex identity governance and access management requirements.
Develop integrations between Saviynt and enterprise platforms, including ServiceNow, CyberArk, and application ecosystems.
Translate existing governance processes, workflows, and access models into scalable Saviynt solutions.
Support entitlement aggregation, reconciliation, testing, deployment, and production-readiness activities.
Create technical documentation, implementation guides, operational procedures, and audit evidence.
Collaborate with engineering teams, architects, and professional services partners to deliver roadmap commitments and platform modernization initiatives.
Provide technical leadership and mentorship while driving engineering best practices across the IGA ecosystem.
Use AI-assisted development and analysis tools to accelerate system design, coding, testing, analysis, and troubleshooting.
Validate AI-assisted outputs using sound technical judgment; account for model limitations, security risks, and operational considerations.
Apply AI responsibly in development and production environments and ensure usage aligns with security, compliance, privacy, and ethical standards.
Follow applicable risk programs, policies, procedures, and risk and compliance obligations; monitor, identify, escalate, and remediate issues as appropriate.