Intelligent Automation Engineer

Role Title: Intelligent Automation Engineer

Division: Technology 

Location: Glasgow, Liverpool, London 

Reports to: Automation Product Owner 

Working Pattern: Hybrid

About the Role

Design, build, and operate intelligent automation, AI-enabled, document processing, workflow, and data solutions that transform how the organisation processes information, reviews complex records, and delivers operational outcomes. Combining artificial intelligence, data engineering, intelligent document processing, workflow automation, and analytics, you will develop scalable solutions that improve quality, speed, efficiency, and decision-making across business processes whilst maintaining robust governance, traceability, auditability, and regulatory controls.

The Intelligent Automation Engineer will deliver AI-enabled workflows, digital assistants, intelligent review solutions, and data-driven automation capabilities grounded in enterprise information. Working across structured and unstructured data sources, you will automate document-centric processes, extract actionable insights, support remediation and review activities, and enable colleagues to manage high-volume casework more effectively and consistently.

A key focus of the role will be supporting complex review, remediation, and transformation programmes through the extraction, analysis, and interpretation of data across large client populations. This includes developing solutions to identify and analyse cohorts, review client and portfolio data, monitor process outcomes, generate management information, and provide comprehensive audit trails that support business, regulatory, and operational requirements.

The role offers a unique opportunity to contribute to a major multi-year transformation programme through to early 2028, delivering innovative AI, automation, workflow, document processing, and data solutions that support large-scale review, remediation, and operational change activities. During this period, you will play a key role in shaping and delivering technology capabilities that improve how the organisation manages complex data, information, and client review processes.

Following the transformation programme, the role will transition into a long-term position within the Intelligent Automation team, taking ownership of enterprise automation, AI, workflow, and data platforms. You will be responsible for driving continuous improvement, supporting operational excellence, maintaining strong governance and platform stability, and helping shape the future automation and AI strategy of the organisation. This provides a unique blend of transformational programme delivery and sustainable platform ownership, offering both immediate business impact and long-term career development within a growing Intelligent Automation capability.

What You'll Be Responsible For

• AI & Intelligent Automation Engineering - Design and deliver secure, reliable AI-enabled solutions, digital assistants and intelligent workflows that orchestrate tasks, decisions and integrations across enterprise systems.
• Generative AI & Knowledge Solutions - Develop AI-powered solutions that leverage organisational knowledge and enterprise data to provide summarisation, question answering, insight generation and decision support capabilities whilst maintaining appropriate governance and controls.
• Intelligent Document Processing - Design and implement solutions that extract, classify and structure information from unstructured and semi-structured content, including documents, forms, correspondence, reports and records. Utilise OCR and document processing technologies to reduce manual effort and improve consistency.
• AI-Assisted Review, Remediation & Analysis - Develop AI-powered workflows supporting large-scale review, remediation, validation and quality assurance activities. Combine structured data, business rules and AI techniques to identify exceptions, surface insights, summarise findings and support decision-making through appropriate human oversight.
• Identification & Management Information - Design solutions that analyse large datasets to identify review populations, client cohorts and operational trends. Develop repeatable processes to extract, calculate and report key management information.
• Data Engineering & Transformation - Build data pipelines that collect, cleanse, enrich and transform information from multiple sources. Ensure data quality, traceability and accessibility for automation, AI and analytical solutions.
• Workflow & Case Management - Design end-to-end workflows that combine automated processing, business rules, human review, approvals, exceptions and operational controls.
• Systems Integration - Integrate automation and AI solutions with internal and third-party systems through APIs, data services, event-based patterns and secure data exchange mechanisms.
• Quality, Reliability & Support - Develop testable, supportable solutions that are instrumented for monitoring, auditing and operational support. Continually improve performance through measurement, feedback and iterative delivery.
• Governance, Risk & Compliance - Apply security-by-design principles, data protection controls, AI governance requirements and risk management practices. Maintain technical documentation, operational runbooks, version control and audit trails.
• Process Design & Optimisation - Partner with business stakeholders and subject matter experts to understand current and future-state processes. Identify opportunities to leverage AI, workflow automation, intelligent document processing and digital technologies to improve outcomes.
• Continuous Improvement - Stay current with emerging AI and automation capabilities. Contribute to standards, reusable frameworks, best practices and knowledge sharing across the automation community.

About You

• Strong problem-solving skills with a pragmatic and outcome-focused approach.
• Comfortable working in ambiguity and rapidly iterating solutions to deliver measurable business value.
• Excellent communication skills, capable of explaining technical concepts and trade-offs to both technical and non-technical audiences.
• Experience translating complex business requirements into scalable AI, data, workflow and automation solutions.
• Strong analytical mindset with the ability to interpret business rules, identify patterns and derive insights from large volumes of information.
• Understanding of how AI, automation and human oversight can be combined within regulated environments.
• Disciplined engineering practices, including testing, documentation, monitoring and secure development standards.
• Experience working with document-centric processes, complex datasets and operational workflows.
• Experience supporting large-scale review, remediation, assurance or operational improvement initiatives through the analysis of structured and unstructured datasets, generation of management information and identification of key trends, cohorts and exceptions.

Technical Stack – Essential

• Artificial Intelligence & Machine Learning - Experience developing and implementing AI-powered solutions, including large language models, knowledge-based assistants, retrieval techniques, prompt optimisation, evaluation frameworks, content safety controls and AI governance practices.
• Intelligent Document Processing - Experience with OCR, document classification, information extraction, form recognition, data capture, document intelligence and validation technologies.
• AI Validation & Quality Assurance - Experience evaluating AI outputs, implementing confidence scoring, designing human-in-the-loop review processes and measuring solution performance against defined business outcomes.
• Workflow Automation - Experience designing and building workflow automations that combine business rules, user actions, approvals, exception handling and system integrations.
• Data Engineering & Analytics - Strong data manipulation skills. Experience cleansing, transforming, validating and reconciling structured and unstructured datasets from multiple sources.
• Integration Technologies - Experience working with APIs, JSON, webhooks, authentication, secure data exchange, event-driven patterns, exception handling and resilient integration design.
• Software Engineering Fundamentals - Experience with version control, release management, environment management, reusable components, configuration management, testing and secure secrets handling.
• Governance, Risk & Compliance - Understanding of data protection, auditability, access controls, AI governance, model risk considerations, operational resilience and secure delivery standards.

Technical Stack – Desirable

• Robotic Process Automation - Experience with robotic process automation or desktop automation technologies for legacy, rules-based or user-interface driven automation scenarios.
• Advanced AI Architecture - Experience designing and implementing scalable AI architectures, semantic retrieval capabilities, vector-based search, orchestration frameworks and agentic AI patterns.
• Analytics & Visualisation - Experience creating dashboards, management information reporting, telemetry visualisation and operational analytics that support decision-making, review activities and performance monitoring.
• Testing & Quality Engineering - Experience with automated testing frameworks, integration testing, contract testing and performance testing.
• Front-End Development - Experience building internal applications, workflow interfaces or AI-enabled user experiences using appropriate front-end or low-code technologies.
• Regulated Industry Experience - Experience delivering AI, automation, remediation, review or quality assurance solutions within financial services, wealth management, compliance or regulated environments.

Measures of Success

• Business Outcomes - AI-enabled automations and document intelligence solutions are delivered safely into production, providing measurable improvements in efficiency, quality, accuracy and colleague experience.
• Review & Processing Efficiency - Document review and information processing activities are significantly accelerated through automation whilst maintaining appropriate levels of accuracy and governance.
• Data Quality & Traceability - Solutions provide consistent, auditable extraction and processing of information with clear lineage, validation controls and exception management.
• Security & Compliance - Solutions are secure, compliant and supportable, with documented runbooks, controlled access, monitored performance and auditable change histories.
• Scalability & Reusability - Automation, AI and document intelligence capabilities are delivered using reusable patterns, connectors and components that accelerate future delivery.
• AI Governance & Transparency - AI solutions provide explainable outcomes, appropriate human oversight and measurable quality controls that align with organisational governance standards.
• Operational Performance - Solutions deliver measurable improvements in throughput, cycle times, operational capacity and service quality across supported business processes.