AI Engineer, VP
Mitsubishi UFJ Financial Group2 hours ago
London, United KingdomStaff+
Responsibilities
- Identify and prioritize AI opportunities with measurable productivity, quality, control, risk, and service outcomes.
- Analyze workflows with business leaders and process owners, quantify benefits, define success measures, and create delivery roadmaps.
- Build, configure, and integrate generative AI, agentic workflows, retrieval-augmented generation, workflow automation, analytics, and decision-support solutions.
- Design human-in-the-loop controls, explainability, validation, testing, monitoring, exception handling, evidence capture, and audit trails into AI-enabled processes.
- Align local solutions with MUFG AI governance, model risk, information security, data privacy, regulatory, records management, and operational resilience requirements.
- Collaborate with Global Markets AI and the AI Centre of Excellence to reuse platforms, models, controls, patterns, and engineering standards.
- Deliver prototypes and production solutions, track adoption and benefits, and provide user training, documentation, and responsible-use guidance.
- Escalate risks and control gaps and coordinate approvals with technology, data, cyber, legal, risk, finance, and operational teams.
Requirements
- 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 through analysis, 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 with software engineering practices including version control, CI/CD, testing, documentation, peer review, and release management.
- Strong Python development skills and experience writing maintainable, tested, and documented code.
- SQL and database experience covering data extraction, transformation, validation, and integration.
- Experience with APIs, workflow integration, secure system-to-system connectivity, cloud architecture, and enterprise data platforms.
- Strong understanding of generative AI, prompt design, model selection, retrieval-augmented generation, embeddings, evaluation, hallucination risk, guardrails, and responsible AI controls.
- Ability to design agentic or semi-agentic workflows with human oversight, logging, validation, and exception handling.
- Ability to define test plans and acceptance criteria for functional, regression, model, prompt, and control testing.
- Preferred qualifications include enterprise generative or agentic AI delivery, vector search, knowledge management, document intelligence, workflow orchestration, banking or capital markets experience, AI platforms, model evaluation tools, AI governance, and regulated compliance or surveillance knowledge.
- Relevant cloud, data, AI, cyber, risk, agile, or project delivery certifications are preferred.
- A degree in Computer Science, Engineering, Data Science, Mathematics, or a related field, or equivalent practical work experience, is required.
- Excellent communication, stakeholder engagement, judgment, problem-solving, prioritization, documentation, analytical, and workload-management skills are required.
Benefits
- Flexible working requests are considered in line with organizational requirements.
- MUFG supports diversity, equality, inclusion, and a non-discriminatory recruitment and employment environment.