AI Engineer

Salary: £40,000 - 80,000 per year

Requirements:

• Computer Science, Engineering, Data Science, Mathematics or related degree, or equivalent practical work experience.
• Relevant cloud, data, AI, cyber, risk, agile or project delivery certifications are preferred.
• Experience designing, building or implementing AI, generative AI, automation, analytics or data-driven workflow solutions in a corporate or financial services environment.
• Practical experience translating business requirements into engineered solutions, including process analysis, solution design, build, testing, deployment and adoption support.
• Experience working with governance, risk, compliance, information security, data privacy or control requirements in a regulated environment.
• Experience using modern software engineering practices, including version control, CI/CD, testing, documentation, peer review and release management.
• Experience working with business stakeholders and technology teams to deliver measurable outcomes under time, budget, policy and control constraints.
• Experience implementing generative AI or agentic AI solutions in enterprise environments is preferred.
• Experience with retrieval-augmented generation, vector search, knowledge management, document intelligence or workflow orchestration is preferred.
• Experience in banking, capital markets, financial services or another highly regulated industry is preferred.
• Experience with cloud platforms, data platforms and enterprise integration patterns is preferred.
• Strong understanding of generative AI concepts, including prompt design, model selection, RAG, embeddings, evaluation, hallucination risk, guardrails and responsible AI controls.
• Ability to design and implement agentic or semi-agentic workflows with appropriate human oversight, logging, validation and exception handling.
• Strong Python development skills and ability to build maintainable, tested and documented code.
• SQL and database experience, including data extraction, transformation, validation and integration.
• Experience with APIs, workflow integration and secure system-to-system connectivity.
• Practical understanding of cloud-based programming and architecture, particularly Azure; AWS experience is also beneficial.
• Experience with enterprise data platforms such as Snowflake or equivalent.
• Use of AI-assisted engineering tools such as GitHub Copilot, Claude Code or equivalent agentic coding harnesses, with appropriate review and control of generated outputs.
• Use of industry-standard CI/CD and software delivery tools such as Git, TeamCity, deployment automation and issue-tracking platforms.
• Understanding of secure software development, data classification, access control, secrets management and auditability.
• Ability to define test plans and acceptance criteria for AI-enabled solutions, including functional testing, regression testing, model and prompt evaluation, and control testing.
• Ability to communicate technical concepts clearly to non-technical stakeholders and convert functional problems into practical solution designs.
• Experience with AI orchestration frameworks, model evaluation tooling, vector databases, document processing, knowledge retrieval or workflow automation platforms is preferred.
• Familiarity with model risk management, AI governance, EU AI Act concepts, data privacy and regulatory expectations for AI in financial services is preferred.
• Understanding of process improvement methods and benefits realisation, including baselining, KPI definition and post-implementation measurement is preferred.
• Conduct risk, market abuse, surveillance and communications monitoring concepts are preferred.
• AML, sanctions, KYC and transaction monitoring control concepts are preferred.
• Personal account dealing, outside interests, gifts, entertainment and conflicts concepts are preferred.
• Regulatory training, attestations, policy management and evidence tracking concepts are preferred.
• Workforce analytics, skills data and compensation governance considerations are preferred.
• Data privacy, employment law sensitivity, fairness and bias risk in AI models are preferred.
• Investigation workflows, case management and defensible audit trails are preferred.
• Excellent communication skills, including the ability to engage senior stakeholders and explain AI risks and opportunities clearly.
• Results driven, with a strong sense of accountability and ownership.
• Proactive and motivated, with the ability to identify opportunities and drive them through to delivery.
• Ability to operate with urgency and prioritise work according to business value, risk and delivery constraints.
• Strong decision-making skills and sound judgement, especially where AI outputs affect controls, decisions or regulated processes.
• Structured and logical approach to problem solving.
• Creative and innovative mindset, balanced with strong risk awareness and control discipline.
• Excellent interpersonal skills and ability to work across functions, technology, risk, compliance and governance teams.
• Ability to manage large workloads and tight deadlines.
• Excellent attention to detail and accuracy.
• Calm approach, with the ability to perform well in a pressurised environment.
• Strong numerical and analytical skills.
• Strong Microsoft Office skills and ability to produce clear documentation, presentations and process materials.

Responsibilities:

• Prioritise and deliver AI opportunities within specific product lines, focusing on measurable productivity, quality, risk, control and service outcomes.
• Partner with leaders and process owners to assess current workflows, identify pain points, quantify benefits, define success measures and create practical delivery roadmaps.
• Build, configure and integrate AI solutions using approved enterprise platforms, tools and patterns, including generative AI, agentic workflows, RAG, prompt orchestration, workflow automation and data-driven decision support.
• Ensure solutions comply with our AI governance, model risk, information security, data privacy, records management, regulatory, compliance and operational resilience requirements.
• Design controls into AI-enabled processes, including human-in-the-loop review, explainability, validation, testing, monitoring, exception handling, evidence capture and audit trails.
• Collaborate with Global Markets AI and the AI CoE to reuse common components, contribute reusable patterns and ensure local delivery remains aligned to enterprise AI architecture and engineering standards.
• Work with technology, data, cyber, legal, risk, finance and operational teams to obtain required approvals and ensure solutions are supportable, secure and scalable.
• Deliver rapid prototypes and quick wins where appropriate, while ensuring production solutions meet engineering, governance and control expectations.
• Track benefits and adoption after implementation, including run-rate savings, productivity uplift, quality improvement, cycle-time reduction, risk reduction and user engagement.
• Provide training, documentation and practical guidance to users so AI tools are used responsibly, consistently and effectively.
• Maintain awareness of emerging AI capabilities and assess their relevance in a controlled and commercially practical manner.
• Escalate risks, issues, control gaps or conflicts of priority promptly through the functional reporting line, Global Markets AI and AI CoE governance channels.
• Work closely with process owners, risk and control stakeholders, technology teams, data owners, Global Markets AI and the AI CoE to identify, design, build and embed AI solutions that improve productivity, control effectiveness, employee and conduct governance, decision support and operational resilience.
• Support the control environment, conduct framework, workforce governance and regulatory expectations for employees operating across Bank and Securities entities.

Technologies:

• Agentic AI
• AI
• AWS
• Azure
• CI/CD
• Claude Code
• Cloud
• Copilot
• Git
• GitHub
• Support
• Python
• RAG
• SQL
• Security
• Snowflake
• Teamcity
• Embedded

More:

Mitsubishi UFJ Financial Group (MUFG) is one of the worlds leading financial groups, with around 150,000 colleagues across the globe working to make a difference for every client, organization and community we serve. We are committed to long-term relationships, serving society and fostering shared, sustainable growth for a better world. Our culture puts people first, values diverse ideas and collaboration, and invests in talent, technology and tools so our people can own their careers. The role sits within GMEO (Global Markets Engineering Office), where Global Markets AI provides engineering capability, delivery discipline and scalable technology enablement, and the AI Centre of Excellence defines enterprise standards for responsible AI adoption across MUFG. The Function Aligned AI Engineer role is based in London, full time, and we are open to considering flexible working requests in line with organisational requirements. We are committed to diversity, inclusion and non-discriminatory recruitment and employment.

last updated 34 week of 2026