Lead AI Software Engineer

Overview

In this AI Engineer role, you design, build, and deliver AI-enabled applications and agentic systems that connect frontend UIs with backend services and MCP infrastructure. You will work across full stack to implement scalable, secure, observable AI solutions in enterprise settings. You collaborate with AI developers, platform engineers, and product teams to create reusable MCP-enabled patterns and agent-driven workflows. You’ll tackle complex integration, security, and deployment challenges to enable production-ready AI capabilities. This role offers the opportunity to shape enterprise AI tooling and workflows at scale within Wells Fargo’s platform standards.

Responsibilities

• Deliver end-to-end AI application features using MCP services and agent orchestration layers
• Own and contribute to MCP service implementations, including tool schema design and deployment readiness
• Build MCP-compatible tools, skills, APIs, and UI components for cross-application use
• Integrate AI-powered UIs with backend APIs, MCP servers, RAG systems, and agent workflows
• Implement RBAC policies governing tool/access usage
• Develop agent workflows for complex, multi-step objectives via MCP and skill orchestration
• Align solutions with enterprise platform standards (security, observability, testing, deployment)
• Ensure frontend performance, accessibility, and maintainability with reusable design patterns
• Ensure backend/AI services are scalable, observable, and deployable on OpenShift/Kubernetes
• Write technical documentation, API specs, and runbooks
• Contribute to engineering best practices (code reviews, CI/CD, monitoring, production support)

Key requirements

• Strong proficiency in Python with Fast MCP, FastAPI, and Flask
• Experience building REST/async/event-driven services
• Experience integrating with AI/LLM systems and agent platforms
• Experience with React and TypeScript for frontend
• Experience with authentication/authorization patterns (SSO, OAuth2, API keys, RBAC, scopes)
• Experience with MCP servers and understanding MCP protocol (tool registration, schemas, flows)
• Experience developing agent-driven workflows with LangChain, Google ADK, or similar
• Frontend fundamentals (HTML, CSS, JS, DOM, performance)
• Experience automated testing (Playwright), performance testing, code reviews, CI/CD
• Experience building secure, scalable enterprise apps aligned with standards

• Cross-functional collaboration
• Problem solving and initiative
• Attention to security and governance
• MCP servers and MCP protocol
• LangChain Deep Agents or similar agent frameworks
• RAG systems, vector search, embeddings

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