Principal Engineer, AI Engineering

Salary: £41,000 - 81,000 per year

Requirements:

• We require technology strategic leadership experience, or equivalent demonstrated through a combination of work experience, training, military experience, or education.
• We require expert-level hands-on engineering experience with AI development in Python, TypeScript, React, APIs, distributed high-performance systems, and application delivery.
• We require deep experience designing and delivering AI-enabled applications using agentic workflows, LLMs, RAG, model orchestration, embeddings, vector search, and model evaluation techniques.
• We require experience with OpenAI, Anthropic, Google Vertex AI, GitHub Copilot, or related AI developer ecosystems.
• We require a proven ability to influence technical strategy across teams without relying solely on direct reporting authority.
• We require a strong understanding of cybersecurity controls, data privacy, model risk management, governance, and compliance expectations in regulated financial-services environments.
• We require in-depth knowledge of industry trends and thought leadership in the development of AI solutions.

Responsibilities:

• We serve as a senior technical authority for AI engineering strategy, architecture, and implementation across complex, multi-domain initiatives.
• We design, build, and guide enterprise-grade AI systems including RAG platforms, agentic workflows, chat experiences, orchestration layers, evaluation pipelines, and reusable AI services.
• We establish scalable, secure, and compliant architecture patterns for agentic solutions using industry standard frameworks.
• We provide hands-on technical leadership across MCP, Python, TypeScript, React, APIs, OpenShift, Kubernetes, and CI/CD engineering practices.
• We build AI solutions including agents, chatbots, RAG and knowledge platforms, skill-based agents, workflow automation, and AI-enabled developer experiences.
• We define engineering standards for prompt engineering, skill engineering, model evaluation, observability, guardrails, red teaming, hallucination detection, and responsible AI adoption.
• We partner with engineering leads, product owners, cybersecurity, governance, risk, platform, and UI/UX teams to align technical direction with strategic business outcomes.
• We mentor senior engineers and technical leads through architecture reviews, code reviews, reusable patterns, technical coaching, and design governance.
• We resolve complex technical challenges across AI pipelines, model integrations, infrastructure, application resiliency, security controls, and production operations.
• We define target-state architecture, reusable design patterns, and technical standards for AI systems.
• We guide architecture decisions across model integration, retrieval design, orchestration, workflow automation, security, observability, and application experience layers.
• We evaluate emerging AI technologies and translate them into practical, governed, production-ready engineering patterns.
• We lead proof-of-concepts, design reviews, code reviews, and technical deep dives for high-impact AI initiatives.
• We establish best practices for AI applications in coding, API design, testing, deployment automation, runtime monitoring, and operational readiness.
• We improve developer productivity through reusable libraries, templates, reference implementations, and engineering enablement.
• We ensure AI systems are designed with appropriate controls for security, data protection, access management, auditability, and model risk.
• We define and promote responsible AI practices including evaluation, explainability considerations, fallback behavior, guardrails, and human-in-the-loop review where appropriate.
• We partner with cybersecurity, governance, compliance, and platform teams to ensure solutions meet enterprise and regulatory expectations.
• We influence cross-team technical decisions and align stakeholders around scalable, secure, and maintainable AI engineering approaches.
• We mentor senior engineers and engineering leads through technical coaching, architecture guidance, and hands-on problem solving.
• We communicate technical trade-offs, risks, delivery considerations, and architectural direction to senior leaders and cross-functional partners.

Technologies:

• Agentic AI
• AI
• API
• CI/CD
• Copilot
• GitHub
• Support
• Kubernetes
• MCP
• OpenShift
• Python
• RAG
• React
• Security
• TypeScript
• UX UI Design
• ElasticSearch
• Redis

More:

We are Wells Fargo, seeking a Principal Engineer in Corporate and Investment Banking to serve as a senior technical authority for AI solutions. This is a full-time hybrid role based in the City of London. We offer a position focused on secure, resilient, and governed agentic AI systems, with relocation assistance not available and visa sponsorship not available. We value equal opportunity, support a strong risk-mitigating and compliance-driven culture, and emphasize proactive monitoring, governance, risk identification and escalation, and sound risk decisions. We also maintain a drug-free workplace. The posting end date is 26 Sep 2026, and applications may close early due to applicant volume.

last updated 36 week of 2026