Senior AI Engineer

Salary: £40,000 - 80,000 per year

Requirements:

• Significant experience designing, building or governing AI, generative AI, agentic AI, automation or data-driven platforms in a regulated enterprise environment
• Experience delivering reusable platform capabilities, shared engineering frameworks, enterprise components or developer enablement tooling
• Experience working with governance, model risk, compliance, information security, data privacy, audit, operational resilience or control requirements in financial services or another regulated industry
• Strong experience with modern software engineering practices, including architecture, version control, CI/CD, testing, peer review, security scanning, release management and production support
• Experience working with senior business, technology, risk, compliance and control stakeholders to deliver measurable outcomes under policy, control and delivery constraints
• Experience delivering capabilities that span multiple functions, systems, data domains, control owners or legal entities
• Experience in Global Markets, investment banking, capital markets, trading, sales, risk, finance, operations or securities processing environments
• Experience with AI governance frameworks, model inventory, model risk management, prompt/model evaluation, responsible AI, AI risk classification or regulatory expectations for AI
• Experience with governed enterprise data platforms, data catalogues, query gateways, entitlement controls, data lineage and audit logging
• Experience designing secure integrations with enterprise systems such as JIRA, Azure DevOps, OpenPages/GRC, ServiceNow, SharePoint, Confluence, Git, IAM, SIEM or observability platforms
• Experience training, certifying or enabling distributed engineering communities, citizen developers or function-aligned delivery teams
• Experience with MLOps, LLMOps, monitoring, evaluation, drift detection, incident management, change control and lifecycle management for AI-enabled applications
• Deep understanding of generative AI concepts, including prompt design, model selection, RAG, embeddings, vector search, tool use, agentic orchestration, evaluation, hallucination risk and guardrails
• Ability to design AI solutions with appropriate access control, audit logging, data classification, DLP, secrets management, human oversight, exception handling, monitoring and evidence capture
• Strong Python development skills and ability to build maintainable, tested, documented and supportable enterprise code
• Ability to design reusable frameworks, platform services, APIs, SDKs, templates and reference implementations for distributed delivery teams
• Strong understanding of cloud-based programming and architecture, particularly Azure; AWS experience is also beneficial
• SQL and database experience, including enterprise data access, transformation, validation, data lineage and integration with platforms such as Snowflake, Starburst or equivalent
• Strong use of industry-standard CI/CD and software delivery tools such as Git, TeamCity, deployment automation, issue tracking and release governance
• Advanced use of AI-assisted engineering tools such as GitHub Copilot, Claude Code or equivalent agentic coding harnesses, with appropriate review, testing and control of generated outputs
• Ability to define test strategies for AI-enabled solutions, including functional testing, regression testing, prompt/model evaluation, adversarial testing, UAT, control testing and release evidence
• Ability to communicate complex technical, governance and risk concepts clearly to senior stakeholders and convert strategic objectives into practical delivery patterns
• Computer Science, Engineering, Data Science, Mathematics or related degree, or equivalent practical work experience
• Relevant cloud, data, AI, cyber, risk, architecture, agile or project delivery certifications
• Ability to balance speed, innovation, governance, security, resilience and commercial value in a regulated banking environment
• Excellent communication skills, including the ability to engage senior stakeholders and explain AI architecture, risks and opportunities clearly
• Ability to influence distributed teams, set standards, coach engineers and drive adoption without owning every local delivery outcome
• Results driven, with a strong sense of ownership for platform quality, controls, adoption and measurable outcomes
• Proactive and motivated, with the ability to identify strategic opportunities and drive them through to controlled delivery
• Ability to prioritise according to business value, risk, regulatory impact, operational resilience and delivery constraints
• Strong decision-making skills and sound judgement, especially where AI outputs affect controls, decisions, regulated processes or production systems
• Structured and logical approach to complex, cross-functional problem solving
• Excellent interpersonal skills and ability to work across Technology, Risk, Compliance, Legal, Finance, Operations, Front Office and governance teams
• Excellent attention to detail and documentation quality
• Creative and innovative mindset, balanced with strong risk awareness and control discipline

Responsibilities:

• Lead the engineering design and delivery of Lane 3 enterprise AI capabilities for Global Markets AI, ensuring solutions meet full enterprise architecture, security, governance and operational standards
• Define, maintain and continuously improve AIQ engineering standards, reusable patterns, control requirements and reference architectures for Global Markets AI adoption
• Own or support technical governance for AI intake, risk classification, lane routing, architecture review, threat modelling, model and prompt evaluation, release approval and production monitoring
• Build reusable AI platform components, including RAG frameworks, agentic workflow patterns, connector patterns, evaluation harnesses, logging, audit trails, evidence packs and deployment templates
• Partner with Lane 2 Function Aligned AI Engineers to review designs, unblock engineering issues, promote reuse and ensure local function-built solutions remain aligned to CoE standards
• Enable Lane 1 citizen-led delivery by providing safe templates, guardrails, training, certification, review processes and controlled runtime patterns
• Maintain AI inventory quality and ensure production AI solutions have clear ownership, documentation, data lineage, access control, monitoring, support model and lifecycle status
• Design and govern AIQ integrations with enterprise tools and data sources, including entitlement controls, DLP, audit logging, read-only execution constraints and operational resilience requirements
• Work with Technology, Cyber, Risk, Compliance, Legal, Finance, Operations and Front Office stakeholders to ensure AI adoption is safe, supportable, auditable and aligned to Bank and Securities entity obligations
• Ensure AI-enabled solutions include human oversight, explainability, validation, testing, exception handling, evidence capture and escalation paths proportionate to risk
• Track and evidence benefits from CoE platform and Lane 3 delivery, including NOP contribution, productivity uplift, cost reduction, control improvement, cycle-time reduction and operational resilience
• Maintain awareness of emerging AI, agentic engineering, model evaluation, governance and enterprise platform capabilities, assessing their relevance to Global Markets in a controlled and commercially practical manner

Technologies:

• Agentic AI
• AI
• AWS
• Azure
• CI/CD
• Claude Code
• Cloud
• Copilot
• Confluence
• DevOps
• Git
• GitHub
• IAM
• Incident Management
• Support
• JIRA
• MLOps
• Python
• RAG
• SQL
• Security
• ServiceNow
• SharePoint
• Snowflake
• Teamcity
• API
• Fabric
• MCP

More:

We are Mitsubishi UFJ Financial Group (MUFG), one of the worlds leading financial groups, with around 150,000 colleagues across the globe. Our culture is built on putting people first, listening to diverse ideas and collaborating to create greater innovation, speed and agility. We aim to be the worlds most trusted financial group by investing in talent, technologies and tools that help our people own their careers and make a meaningful impact. Our GMEO (Global Markets Engineering Office) provides engineering capability, delivery discipline and scalable technology enablement for Global Markets, and our Global Markets AI team leads AI strategy, engineering standards, reusable delivery patterns and responsible AI adoption. The Global Markets AI Centre of Excellence provides the platform, standards, controls and enablement model that allow applied AI adoption to scale safely across Global Markets from experimentation to a governed operating model. This full-time role is based in London, and we are open to considering flexible working requests in line with organisational requirements. Our advert closes on 28th August 2026. We are committed to diversity, inclusion and equal opportunity, and we make recruitment decisions in a non-discriminatory manner.

last updated 35 week of 2026