Wells Fargo
CITY OF LONDON,
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 readines
Required qualifications
Specialty Software Engineering experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education
Strong proficiency in Python with experience building services using frameworks such as Fast MCP, FastAPI & Flask.
Experience developing and integrating with REST APIs, asynchronous services, and event-driven architectures.
Experience integrating with AI, LLM-based systems, agent platforms, or AI APIs.
Experience with React and TypeScript for building frontend applications.
Experience with authentication, authorization, and access control patterns, including SSO, OAuth 2.0, API keys, token-based access, RBAC, and scopes.
Experience building or integrating with MCP servers & understanding of MCP protocol, including tool registration, schemas, message flows, clients, servers, and lifecycle patterns.
Experience developing agent-driven workflows using frameworks such as LangChain, Google ADK, or similar orchestration frameworks.
Experience frontend fundamentals, including HTML, CSS, JavaScript, browser rendering, DOM APIs, and performance tuning.
Experience with automated testing with Playwright, performance testing, code reviews, and CI/CD practices.
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.
Posting End Date:
26 Sep 2026
*Job posting may come down early due to volume of applicants.
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.
Candidates applying to job openings posted in Canada: Applications for employment are encouraged from all qualified candidates, including women, persons with disabilities, aboriginal peoples and visible minorities. Accommodation for applicants with disabilities is available upon request in connection with the recruitment process.
To request a medical accommodation during the application or interview process, visit
Disability Inclusion at Wells Fargo
.
Wells Fargo maintains a drug free workplace. Please see our Drug and Alcohol Policy to learn more.
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