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Wells Fargo Logo Wells Fargo · IT - Software Development

Lead Specialty Software Engineer - AI Tooling & Enablement

United States, Charlotte · Job Posted June 15, 2026
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Job Description

Wells Fargo is seeking a Specialty Software Engineer to support the onboarding, adoption, and enablement of AI tools and software development lifecycle (SDLC) technologies across the Chief Data Office (CDO). This role will focus on accelerating engineering productivity, fostering technical communities, and promoting innovative practices through events such as hackathons and internal forums.

Job Responsibility

  • 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

  • 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

Nice to have

  • Prompt & playbook engineering — building reusable macros/playbooks, scoping tasks well for agents
  • Understanding agent capabilities & limits — knowing what tools do does well vs. poorly
  • Knowledge/context management — capturing coding conventions, architecture, gotchas as persistent knowledge notes
  • Developer advocacy / enablement — running workshops, demos, office hours
  • this is a people-facing adoption role, not just engineering
  • Technical writing & documentation
  • Metrics & ROI storytelling — tracking adoption, PR merge rates, time saved, and reporting to leadership
  • Stakeholder management & change management — driving behavior change across teams
  • Security & compliance awareness — (PII handling, approval gates, audit)
  • Experience in financial services or other regulated industries
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