Senior AI Software Engineer - MCP & Agentic Systems

Wells Fargo

Hybrid

Quick summary

Work type
Hybrid
Location
Charlotte, NCIselin, NJ
Salary
$100,000–$196,000 / yr
Posted
3 days ago
Closes
Jun 26, 2026
Nearby
99+ roles within 25 mi

Market check

Salary context

Below market

How this pay compares to similar roles

Similar $205k
This role $148k
$81k most similar roles pay here $276k

This role pays less than 86% of similar roles. Most pay $169,700–$239,650 — the shaded band above. At the midpoint, this role pays about $148k versus about $205k for comparable roles.

Based on 240 similar postings.

Employer

About Wells Fargo

Wells Fargo & Company is one of the largest banks in the United States, providing banking, investment, mortgage, and consumer and commercial finance products and services nationwide. Industry: Banking & Financial Services

Wells Fargo currently has 87 open roles on FindRole.

Listed pay typically runs $144,009–$224,000 across 46 roles with salary data.

Most-posted roles

View all roles at Wells Fargo

At a glance

TL;DR · Senior AI Software Engineer - MCP & Agentic Systems

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Wells Fargo is hiring an experienced AI Developer to join their cutting-edge team focused on developing Model Context Protocol (MCP) infrastructure for agentic AI systems. This senior-level position involves designing and implementing MCP servers and clients, ensuring secure access control and authorization within the framework, and building long-running autonomous agents capable of executing complex workflows using tools like LangChain or Google ADK. The ideal candidate will have extensive experience in Python, LLMs, and MCP protocol internals, as well as hands-on knowledge of RESTful APIs, async programming, and event-driven architectures. Additionally, familiarity with containerization, observability tooling, and AI safety principles is essential for this role that demands robust engineering practices and continuous learning in a rapidly evolving field.

Skills

Python FastMCP LangChain Google ADK OAuth 2.0 RESTful APIs async programming OpenTelemetry Pydantic Docker Kubernetes Prompt engineering AI safety principles CI/CD JSON Schema

What you'll do

  • Design and maintain MCP servers using FastMCP for seamless context sharing.
  • Implement MCP clients to integrate with LLM-based applications and agent runtimes.
  • Engineer authorization layers within MCP infrastructure to ensure secure tool exposure.
  • Develop autonomous agents capable of executing complex workflows using LangChain or Google ADK.
  • Build skill-based agents that decompose capabilities into reusable, composable skills.
  • Write technical documentation for MCP infrastructure including integration guides and runbooks.

What we're looking for

  • 4+ years of software engineering experience with proficiency in Python for production-grade services
  • 3+ years of hands-on experience with LLMs, Model Context Protocol (MCP), and long-running agents using LangChain or Google ADK
  • Strong understanding of authentication, authorization, and access control patterns applied to AI tools
  • Experience designing skill-based, modular agents with clear capability boundaries and reusable skills
  • Knowledge of RESTful APIs, async programming, event-driven architectures, and secure access control policies
  • Familiarity with agent observability tooling and containerization for deploying agent services
  • Stay current with the evolving MCP ecosystem and broader agentic AI landscape

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