Lead Specialty Software Engineer – AI Tooling & Enablement

Wells Fargo

Specialty Software Engineer focusing on onboarding and enablement of AI tools in software development. Leading initiatives and mentoring engineers in a hybrid work environment.

Posted 6/10/2026full-timeCharlotte • North Carolina, Texas • 🇺🇸 United StatesSeniorWebsite

Tech Stack

Tools & technologies

AWSAzureCloudDockerGoogle Cloud PlatformJavaKubernetesPythonReactScalaSDLCSparkSpringTypeScript

About the role

Key responsibilities & impact

Drive onboarding, adoption, and effective usage of AI tools and SDLC tooling across engineering teams
Provide technical leadership and guidance on tooling standards, best practices, and integration patterns
Lead complex initiatives related to developer platforms, AI tooling, and engineering productivity
Design, develop, test, and implement tools, utilities, and automation that enhance developer experience and operational efficiency
Mentor junior engineers and provide guidance on tool usage and engineering best practices
Influence team members and stakeholders to adopt new tools and capabilities
Onboarding repos — run repos through the qualifying criteria, create environment blueprints, generate codebase wikis, run proof-of-concept PRs
Building reusable assets — author org-wide and repo-specific playbooks, knowledge notes, and scheduled automations
Running the champions program — train and support per-team tools champions, run 30-min team onboarding workshops, hold office hours
Driving adoption — identify high-value use cases per team, pair with developers, lower the barrier to starting sessions (Teams/GitHub entry points)
Measuring & reporting — own the adoption metrics dashboard (active repos, unique users, PRs/week, merge rate), report ROI to leadership
Governance & best practices — define standards for how a tool is used safely (review requirements, security guardrails, what tasks are/aren't appropriate)
Feedback loop — surface platform gaps/friction back to the vendor and internal infra teams

Requirements

What you’ll need

5+ years of Specialty Software Engineering experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education
5+ years of AI Engineering experience
Hands-on experience using one or more of the following tools: Devin.AI, Claude Code, Cursor.AI, or Github Copilot
Hands-on experience with AI software development tools, CI/CD pipelines, and SDLC processes
Hands-on experience building or supporting GenAI applications, including prompt design and RAG concepts
Familiarity with AI/ML frameworks or orchestration tools (LangChain or similar)
Experience integrating applications with APIs, data platforms, or enterprise systems
Understanding of cloud-based AI services (GCP Vertex AI, AWS, or Azure equivalents)
Experience supporting or implementing developer tooling, platforms, or engineering enablement capabilities
Strong general software engineering — fluency across your org's main stacks (Python/FastAPI, Scala/Spark, Java/Spring, TypeScript/React) so they can validate Devin's output across teams
CI/CD & DevOps — GitHub Actions/Enterprise, build/test pipelines, Docker/Kubernetes; needed to wire repos for reliable Devin sessions
Environment configuration — writing environment blueprints (dependency setup, build/test/lint commands), managing secrets, package registries (Artifactory)
Testing & verification — designing how task completion is measured (test coverage, automated checks) so Devin work is verifiable
Git & code review at scale — branch strategy, PR review, merge-conflict resolution

Benefits

Comp & perks

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Hard Skills & Tools

AI EngineeringSoftware EngineeringGenAI applicationsCI/CD pipelinesSDLC processesAPI integrationCloud-based AI servicesEnvironment configurationTesting & verificationGit & code review

Soft Skills

Technical leadershipMentoringInfluencingCommunicationCollaborationTrainingReportingGovernanceFeedback managementProblem-solving