At a Glance
- Tasks: Design and build next-gen AI applications using cutting-edge technologies.
- Company: Join a leading tech firm focused on innovative AI solutions.
- Benefits: Enjoy competitive pay, flexible work options, and growth opportunities.
- Other info: Hybrid work schedule with excellent career advancement potential.
- Why this job: Make a real impact in the AI space while working with talented teams.
- Qualifications: Strong Python skills and experience with frontend frameworks like React.
The predicted salary is between 63000 - 77000 £ per year.
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:
- 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 with 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.
This position is not eligible for Visa sponsorship. Relocation assistance is not available for this position. Position offers a hybrid work schedule.
Lead AI Software Engineer in London employer: WELLS FARGO BANK
Wells Fargo is an exceptional employer that prioritises employee growth and development, offering a dynamic work culture that fosters collaboration and innovation across the EMEA, APAC, and Canada regions. With a strong commitment to operational resilience and a focus on building robust customer relationships, employees are empowered to make impactful decisions while enjoying comprehensive benefits and support for work-life balance. The company's dedication to diversity and inclusion ensures a welcoming environment where all voices are valued, making it an ideal place for those seeking meaningful and rewarding careers.
StudySmarter Expert Advice🤫
We think this is how you could land Lead AI Software Engineer in London
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We think you need these skills to ace Lead AI Software Engineer in London
Some tips for your application 🫡
Show off your coding skills:When applying for a software engineering role, it's super important to showcase your coding skills. Make sure your CV includes your tech stack, any relevant programming languages you’re comfortable with, and examples of projects you've worked on. If you have a GitHub profile, link it up! We love to see code in action.
Tailor your portfolio:For a full-time role, we’d expect to see some solid examples of your work in your portfolio. Make sure to include at least two or three projects that highlight your problem-solving skills and your ability to work with different technologies. Focus on the projects that are most relevant to the position at WELLS FARGO BANK.
Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at WELLS FARGO BANK and how your skills align with the role. Show us your passion for software development. We dig enthusiastic candidates who understand the value of collaboration and continuous learning!
Be clear and concise:When it comes to writing your CV and cover letter, clarity is key. Avoid jargon that could confuse us and stick to simple, direct language. Highlight your achievements with quantifiable results where possible, and keep everything easy to read. A well-organised application goes a long way!
How to prepare for a job interview at WELLS FARGO BANK
✨Brush Up on Your Coding Skills
For a full-time software engineering role, it's crucial that we stay sharp with our coding abilities. Expect technical questions that might involve solving problems on the spot or discussing algorithms. Practise on platforms like LeetCode or HackerRank to get comfortable with the types of questions that often come up.
✨Know Your Tools and Frameworks
Make sure we’re well-acquainted with the tools and technologies listed in the job description. Familiarise ourselves with any specific frameworks or programming languages mentioned. If WELLS FARGO BANK uses React or Node.js, for instance, be ready to discuss how we’ve used them in previous projects or coursework.
✨Showcase Your Projects
Bring along a portfolio that highlights our best work. This could be code samples, GitHub repositories, or any side projects we’ve built. Make sure we can talk through our thought process for each project, especially the challenges we faced and how we solved them—this shows our problem-solving skills in action.
✨Prepare for Behavioural Questions
While technical skills are key, full-time positions also require cultural fit. Be ready to discuss our previous experiences and how we handle teamwork, conflict, and deadlines. Brush up on the STAR method—Situation, Task, Action, Result—to clearly articulate our past experiences when discussing how we've contributed to a team.
