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Wells Fargo

Lead AI Software Engineer

Wells Fargo is hiring a Lead AI Software Engineer. Level rates it ; you can apply on Wells Fargo.

Level's read on this job

  • On Level's scale, this software engineer role is Builds AI ●●●●: the job is building AI systems.
  • Tools and skills the posting cites include Copilot, LangChain and prompt engineering.
  • Level classifies it as a lead role.
  • Level lists 1,700+ other open roles at Wells Fargo.
  • The role was posted in the last few days.

AI in this role

CopilotLangChain
prompt-engineeringragai-agents

We are seeking an AI Engineer to help design, build, and deliver next-generation AI-enabled applications and agentic systems. This role combines hands-on engineering across frontend applications, Python backend services, MCP infrastructure, agent workflows, and secure enterprise integrations.

As an AI Engineer, you will build user-facing applications and backend services that integrate with Model Context Protocol (MCP) servers, LLM-based applications, RAG-based retrieval systems, and agent orchestration platforms. You will work closely with AI developers, platform engineers, product teams, and other stakeholders to deliver scalable, secure, observable, and production-ready AI solutions.

This engineering role is suited for candidates who can contribute across the full stack while also helping shape reusable patterns for MCP-enabled tools, skills, and agent-driven workflows.


In this role you will

  • Design, build, and maintain AI-enabled applications using React, TypeScript, Python, and modern API frameworks.
  • Develop frontend applications aligned with enterprise UI standards and reusable component patterns.
  • Build and maintain Python backend services, APIs, MCP services, and integration layers using frameworks such as MCP, FastAPI & Flask.
  • Design, implement, and integrate with MCP servers and MCP clients that enable secure context sharing between models, tools, applications, and agent runtimes.
  • Develop and support agentic workflows that execute complex, multi-step tasks using frameworks such as LangChain Deep Agents, Google ADK, or similar agent frameworks.
  • Build skill-based and modular agents that decompose capabilities into reusable, composable, and versioned skills.
  • Build reusable components, services, tool schemas, and integration patterns that can be shared across enterprise AI applications.
  • Integrate logging, tracing, and observability frameworks, including Arize & Splunk compatible logging and agent observability tooling.
  • Ensure applications and services are ready for deployment on enterprise container platforms such as OpenShift or Kubernetes.
  • Collaborate with AI developers, platform engineers, product teams, and architecture partners to deliver robust and scalable AI solutions.

Key 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, tool registration, API integration, authorization enforcement, and deployment readiness
  • Build and maintain MCP-compatible tools, skills, APIs, and UI components for use across AI applications and agent runtimes.
  • Integrate AI-powered user interfaces with backend APIs, MCP servers, RAG systems, and agent workflows
  • Implement RBAC policies governing which users, agents, clients, and applications can invoke specific tools or services.
  • Develop agent workflows that support complex user objectives through mcp & skill orchestration
  • Align solutions with enterprise platform standards, including application scaffolding, security, observability, logging, testing, and deployment practices
  • Ensure frontend applications are performant, accessible, maintainable, and aligned with reusable design patterns.
  • Ensure backend and AI services are scalable, observable, secure, and ready for deployment on OpenShift or Kubernetes-based environments
  • Write and maintain technical documentation, integration guides, API specifications, and operational runbooks
  • Contribute to engineering best practices, including code reviews, automated testing, CI/CD, monitoring, and production support readiness

Required qualifications

  • 5+ years of engineering experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education
  • 5+ years of strong proficiency in Python with experience building services using frameworks such as Fast MCP, FastAPI & Flask
  • 5+ years of experience developing and integrating with REST APIs, asynchronous services, and event-driven architectures
  • 5+ years of experience integrating with AI, LLM-based systems, agent platforms, or AI APIs
  • 5+ years of experience with React and TypeScript for building frontend applications
  • 4+ years of experience with authentication, authorization, and access control patterns, including SSO, OAuth 2.0, API keys, token-based access, RBAC, and scopes
  • 4+ years of experience building or integrating with MCP servers & understanding of MCP protocol, including tool registration, schemas, message flows, clients, servers, and lifecycle patterns
  • 3+ years of experience developing agent-driven workflows using frameworks such as LangChain, Google ADK, or similar orchestration frameworks
  • 3+ years of experience frontend fundamentals, including HTML, CSS, JavaScript, browser rendering, DOM APIs, and performance tuning.
  • 3+ years of experience with automated testing with Playwright, performance testing, code reviews, and CI/CD practices
  • 3+ years of experience building secure, scalable, maintainable applications aligned with enterprise platform standards

Desired qualifications

  • Experience building MCP servers using FastMCP or similar Python-based MCP frameworks
  • Experience designing MCP-compatible tools, reusable skills, and modular agent capabilities
  • Familiarity with tool schema design and structured output validation using tools such as Pydantic, JSON Schema, or Zod
  • Experience with long-running autonomous agents that support retries, state persistence, error recovery, graceful termination, and multi-step workflow execution. Experience with RAG-based retrieval systems, vector search, embeddings, or enterprise knowledge retrieval patterns
  • Experience with agent observability and tracing tools such as LangSmith, OpenTelemetry, Arize, or similar platforms
  • Exposure to Splunk or enterprise observability frameworks
  • Experience with Docker, OpenShift, Kubernetes, or similar containerization and deployment platforms
  • Experience with Copilot Studio, Microsoft Teams UI integration, or conversational application platforms
  • Knowledge of prompt engineering, skill engineering, and knowledge graphs such as llm_wiki and OKF
  • Familiarity with secure enterprise software delivery, platform governance, and reusable engineering standards


Job Expectations:

  • This position is not eligible for Visa sponsorship
  • Relocation assistance is not available for this position
  • Position offers a hybrid work schedule

Job Location Posting:

751 Pinnacle Dr., McLean, VA 22102


Pay Range


Reflected is the base pay range offered for this position. Pay may vary depending on factors including but not limited to demonstrated examples of prior performance, skills, experience, or work location. Employees may also be eligible for incentive opportunities. $191,000.00 - $305,000.00

Benefits

Wells Fargo provides eligible employees with a comprehensive set of benefits, many of which are listed below. Visit Benefits - Wells Fargo Jobs for an overview of the following benefit plans and programs offered to employees.

  • Health benefits
  • 401(k) Plan
  • Paid time off
  • Disability benefits
  • Life insurance, critical illness insurance, and accident insurance
  • Parental leave
  • Critical caregiving leave
  • Discounts and savings
  • Commuter benefits
  • Tuition reimbursement
  • Scholarships for dependent children
  • Adoption reimbursement

Posting End Date:

7 Nov 2026

*Job posting may come down early due to volume of applicants.

We Value Equal Opportunity

Wells Fargo is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, status as a protected veteran, or any other legally protected characteristic.

Employees support our focus on building strong customer relationships balanced with a strong risk mitigating and compliance-driven culture which firmly establishes those disciplines as critical to the success of our customers and company. They are accountable for execution of all applicable risk programs (Credit, Market, Financial Crimes, Operational, Regulatory Compliance), which includes effectively following and adhering to applicable Wells Fargo policies and procedures, appropriately fulfilling risk and compliance obligations, timely and effective escalation and remediation of issues, and making sound risk decisions. There is emphasis on proactive monitoring, governance, risk identification and escalation, as well as making sound risk decisions commensurate with the business unit’s risk appetite and all risk and compliance program requirements.

Applicants with Disabilities

To request a medical accommodation during the application or interview process, visit Disability Inclusion at Wells Fargo.

Drug and Alcohol Policy

Wells Fargo maintains a drug free workplace. Please see our Drug and Alcohol Policy to learn more.


Wells Fargo Recruitment and Hiring Requirements:


a. Third-Party recordings are prohibited unless authorized by Wells Fargo.

b. Wells Fargo requires you to directly represent your own experiences during the recruiting and hiring process.

c. Please be prepared to provide accurate information and supporting documentation in connection with any lawful employment and education verification conducted by Wells Fargo.

How we rate this

Lead AI Software Engineer at Wells Fargo rates 91 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

Prompt engineeringRAGAI agentsCopilotLangChain

Also common in software engineer jobs at this level

Pay

Typical software engineer job
$167k

This posting doesn't list pay. Use the typical software engineer figure when pay comes up. See software engineer jobs

Questions you could be asked

  1. How do you structure and test a prompt to get consistent output from a language model?
  2. How would you design a retrieval step so the model answers from real data instead of guessing?
  3. How do you decide when an AI agent can act on its own versus asking for approval first?
  4. What's a project where you used Copilot hands-on?
  5. Walk me through how you've used LangChain in your day-to-day work.

Adapt your resume

  • List these exact terms on your resume: Prompt engineering, RAG, AI agents, Copilot, and LangChain. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
  • Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.

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