Lead Software Engineer - AI Solutions

Wells Fargo Bank • Concord, CA

1d • Hybrid

About The Position

Wells Fargo is seeking a hands-on technical lead to implement shared AI enablement capabilities supporting Devin and other coding agents across Development, DevOps, and RunOps. The role builds integrations, reusable playbooks, and operational guardrails, and leads complex technology initiatives with broad companywide impact. It reviews large-scale technology solutions against business objectives, enterprise technology environments, and complex technical challenges; develops engineering best practices; and collaborates with technical experts and senior teams to resolve issues and deliver initiatives.

The position owns practical implementation of shared AI engineering capabilities across domain verticals. It converts the AI Enablement Team model into a prioritized engineering backlog; builds secure MCP gateway and tool integrations with access controls, authentication, and audit evidence; enables agent-assisted development and testing workflows with engineer review; and automates delivery processes, ephemeral environments, reversible rollouts, ServiceNow records, and release evidence. It also connects telemetry to incident triage and root-cause analysis, automates runbooks and preventive tests, maintains reusable skills and remediation playbooks, and helps teams adopt them through workshops and pair programming.

The role measures adoption, code acceptance, deployment reliability, MTTD/MTTR, and ACU consumption, while partnering with security and compliance teams to embed guardrails into integrations. The position offers a hybrid work schedule. Visa sponsorship is not available.

Requirements

• At least 5 years of software engineering experience, or equivalent demonstrated through work experience, training, military experience, education, or a combination.
• Experience designing and delivering production software, APIs, and enterprise integrations, with strong coding, automated testing, and troubleshooting skills.
• Experience integrating AI coding agents into development workflows, including pull-request review, generated-code validation, and human approval controls.
• Experience implementing secure tool access using API gateways and Model Context Protocol (MCP), including authentication, authorization, and auditable execution.
• DevSecOps experience with CI/CD pipelines, deployment automation, automated testing, and remediation of code-quality, security, and dependency findings.
• Production reliability experience using telemetry to investigate incidents, establish root cause, improve service-level objectives, and automate operational runbooks.
• Technical leadership ability to translate architecture into working software, lead design and code reviews, mentor engineers, and coordinate delivery across application, platform, and security teams.

Nice To Haves

• Direct experience with Devin, including reusable instructions, agent workflows, and monitoring Agent Compute Unit (ACU) consumption.
• Experience with Apigee Hybrid or ApigeeX and remote or hosted MCP integrations, including enterprise security reviews and access patterns.
• Familiarity with Atlassian Cloud, Figma, GitHub Actions, Sonar, Checkmarx, Black Duck, Harness, Ansible, and ServiceNow.
• Experience with Splunk Observability and AppDynamics, ephemeral test environments, feature-flag rollouts, and automated release-readiness evidence.
• Experience building shared engineering platforms and driving adoption through workshops, pair programming, and communities of champions.

Responsibilities

• Lead complex technology initiatives, including companywide initiatives with broad impact.
• Review and analyze complex, large-scale technology solutions in relation to business objectives, enterprise technology, and technical challenges.
• Develop standard and companywide best practices for engineering and technology solutions, and lead technology teams to deliver initiatives.
• Collaborate with technical experts, senior technology teams, and external industry groups to resolve complex technical issues.
• Convert the shared AI Enablement Team model into a prioritized engineering backlog and deliver reusable capabilities across domain verticals.
• Implement the MCP gateway and tool connectors with appropriate access controls, authentication, and audit evidence.
• Implement agent-assisted story-to-code workflows, pull-request remediation, automated regression testing, cross-browser testing, and performance testing, with engineer review before acceptance.
• Build and maintain pipeline and playbook automation, ephemeral environments, and reversible rollouts, including ServiceNow records and release evidence.
• Connect telemetry to incident triage and evidence-backed root-cause analysis; automate runbooks and preventive tests to reduce repeat incidents.
• Maintain reusable skills, rules, and remediation playbooks, and support engineering-team adoption through workshops and pair programming.
• Monitor adoption, code acceptance, deployment reliability, MTTD/MTTR, and ACU consumption.
• Partner with security and compliance teams to embed guardrails into integrations.

Benefits

• Health benefits
• 401(k) plan
• Paid time off
• Disability benefits
• Life insurance
• Critical illness insurance
• Accident insurance
• Parental leave
• Critical caregiving leave
• Discounts and savings
• Commuter benefits
• Tuition reimbursement
• Scholarships for dependent children
• Adoption reimbursement
• Employees may also be eligible for incentive opportunities.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed