Vanguard

Content Creator

• Develop high-quality, insight-led multimedia content focused on Vanguard 365 (V365) for the UK and Europe
• Design the V365 content experience with Channel Marketing teams, ARC, and external agencies
• Create cohesive client journeys across content asks, channels, and platforms
• Produce engaging, rich, and memorable content experiences for financial advisers and intermediaries
• Use ARC insights and formal external research to develop valuable adviser content
• Ensure content is accurate, compliant, credible, and aligned with brand and house-style guidelines
• Manage the full content lifecycle: ideation, creation, distribution, reuse, and evolution
• Work with Channel Marketers to determine mechanisms for promoting V365 content
• Collaborate with local Channel Marketers to determine and deliver local European needs
• Collaborate with the Client Research Centre on adviser content and face-to-face sessions across Europe
• Become a subject-matter expert on advisers' use of asset-manager content
• Stay current on market developments, investment thinking, and portfolio positioning

Adviser, Content Creator

Artificial Intelligence

• Partner with business stakeholders to identify, frame, and prioritize high-value problems addressable using Agentic AI, LLMs, and NLP
• Translate business needs into AI use cases, success metrics, and delivery plans
• Architect and develop agentic AI systems that reason, plan, and act across tools, workflows, and data sources
• Design multi-agent and tool-augmented LLM solutions for complex, multi-step process automation
• Ensure AI solutions are reliable, explainable, and governed for enterprise use
• Collaborate with engineering teams to deploy scalable, secure, and performant AI solutions
• Implement evaluation, monitoring, and guardrails for LLM and agentic systems, including bias, drift, and failure modes
• Align solutions with enterprise risk management, compliance, and responsible AI standards
• Advise teams on where Agentic AI and LLMs add value
• Contribute to AI best practices, reusable patterns, and strategic direction
• Mentor peers and teammates on applied AI and business-driven problem solving

Senior AI/ML Scientist

Risk

• Define and evolve the enterprise fraud product strategy, roadmap, priorities, and measures of success
• Translate Fraud’s strategic objectives and business-owned requirements into scalable product, data, and technology capabilities
• Lead the product lifecycle from discovery and business-case development through implementation, adoption, measurement, optimization, and enhancement
• Evaluate major initiatives for opportunities to apply artificial intelligence, automation, advanced analytics, shared tooling, and reusable enterprise capabilities
• Guide the selection, integration, and optimization of fraud platforms, including real-time decisioning and rules engines, detection and monitoring, active interdiction, case-management technology, data solutions, and cross-organizational integrations
• Lead product, governance, program capabilities, technology integration, and communications while aligning priorities, resources, dependencies, investment, and execution
• Partner with engineering, architecture, data, risk, compliance, legal, audit, and business leaders to deliver strategic outcomes
• Provide oversight for governance forums, operating rhythms, standards, controls, documentation, escalation paths, and executive reporting
• Build organizational capability through coaching, succession planning, leadership development, and talent management
• Lead a multidisciplinary organization of approximately 18 team members, with anticipated growth to 20–30 members
• Serve as a strategic adviser and execution partner to Fraud leadership

Senior Director, Fraud Product Strategy – Governance

Director

• Lead the design and implementation of strategic supervision initiatives, including supervisory models, escalation frameworks, and role-based oversight structures
• Serve as subject matter expert and program lead for supervision modernization, risk-based monitoring, digital enablement, and control optimization
• Develop and maintain supervisory program documentation, frameworks, operating models, and execution playbooks
• Coordinate cross-functional working groups across Compliance, Risk, Legal, and business stakeholders
• Integrate supervisory controls into business processes, technology platforms, and governance routines
• Monitor industry trends, regulatory developments, and internal risk indicators
• Support regulatory exams, internal audits, and supervisory certifications by preparing documentation and execution evidence
• Provide strategic support to the Head of Supervision on program design, change management, and long-term supervision strategy

Director, Broker Dealer Supervision – Senior Strategist

Software Engineer

• Define and execute the global client identity engineering strategy, target architecture, multiyear roadmap, and investment priorities
• Set the technical vision for identity proofing, authentication, authorization, federation, consent, profile management, digital fraud controls, and identity lifecycle capabilities
• Represent the organization in industry forums and strategic partnerships
• Advise senior executives on identity risk, client experience, platform modernization, resilience, and emerging opportunities
• Lead and develop globally distributed engineering teams across architecture, software development, platform engineering, reliability, testing, implementation, and production support
• Deliver complex, large-scale global identity programs through product, architecture, engineering, security, risk, and business partnerships
• Establish reusable platforms, APIs, software development kits, automation, observability, and engineering standards
• Create an operating model enabling follow-the-sun delivery, clear ownership, consistent quality, capacity management, and rapid issue resolution
• Build a high-performing engineering culture centered on technical excellence, accountability, inclusion, continuous learning, and measurable outcomes
• Lead experimentation, prototyping, threat modeling, and evaluation of emerging technologies and standards
• Convert successful experiments into scalable production solutions
• Develop intellectual property, technical publications, external partnerships, and engineering communities
• Engineer platforms for high availability, horizontal scalability, regional resilience, graceful degradation, disaster recovery, and secure failover
• Embed security, privacy, regulatory, accessibility, and data-minimization requirements throughout the engineering lifecycle
• Strengthen defenses against account takeover, credential compromise, social engineering, identity fraud, session abuse, and AI-enabled threats
• Define service-level objectives, operational readiness criteria, incident response practices, and continuous control validation for critical identity services

Head of Client Identity Engineering

Solutions Engineer

• Lead enterprise deployments, upgrades, integrations, and platform lifecycle activities across the endpoint security ecosystem
• Drive automation, operational excellence, and continuous improvement through engineering best practices, standardization, and process optimization
• Evaluate new technologies and capabilities to ensure scalable, supportable, and secure solutions
• Partner with stakeholders to understand business needs and develop practical endpoint security solutions
• Serve as a subject matter expert for endpoint security technologies and guide solution design across multiple initiatives
• Assess platform dependencies, architectural considerations, and cross-technology impacts when introducing new capabilities
• Lead technical discussions and influence solution direction across engineering, infrastructure, security, and business teams
• Provide guidance on complex technical challenges and communicate recommendations to technical and non-technical audiences
• Contribute to endpoint security strategy, governance, and service ownership practices
• Help lead operational support, stability, and resiliency of enterprise endpoint security platforms
• Drive platform health, monitoring, incident response, vulnerability remediation, and operational risk reduction activities
• Ensure endpoint security services remain reliable, scalable, and effective across a large enterprise environment

Lead Endpoint Security Solution Engineer

Associate

• Consult, collaborate, and work directly with clients on payroll work, full-scale data cleanup in client HRIS, payroll, and Vanguard recordkeeping systems, and conversions
• Own all data-related project work, including problem identification, analysis, resolution, documentation, and internal and external communication
• Manage project inputs; collect, analyze, and determine the appropriateness of client data
• Analyze test data and perform test scenarios to ensure required data is present and accurate
• Review and interpret data for project needs and optimize project approaches related to data
• Interact with prior recordkeepers, payroll vendors, and clients to identify data requirements, resolve data issues, manage project timeframes, and provide guidance on data submissions
• Lead data workflow discussions with internal business partners across Client Administration, Client Services, Participant Education, Risk & Treasury, IT, and Data Transmission Services
• Act as the point of contact and subject matter expert for data-related project functions
• Proactively offer solutions to improve projects and clients’ experiences related to data, data feeds, and processes
• Assist others with issue resolution, training, coaching, and personal development
• Participate in special projects and perform other duties as assigned

Senior Associate, Data Reporting

Engineer

• Support the engineering and operation of the Mac platform across provisioning, configuration, software deployment, compliance, remediation, and lifecycle management
• Engineer and modernize Mac management workflows in Jamf Pro for reliability, scalability, and end-user experience
• Write, maintain, and improve scripts and code supporting Mac platform management, operational efficiency, and service quality
• Participate in peer reviews and team-based engineering practices
• Use AI-assisted development tools such as Copilot and Claude responsibly and effectively
• Evolve Mac endpoint standards including baseline configuration, security settings, compliance guardrails, and lifecycle practices
• Partner with security, QA, and release governance on validation practices for macOS updates, configuration changes, application deployments, and platform releases
• Support and enhance Jamf administration, including policy management, device enrollment, package deployment, troubleshooting, and operational reliability
• Collaborate with the Mac Engineering team and cross-functional Workplace Engineering partners to deliver secure, stable, and scalable platform solutions

Mac Engineer

General

• Develop and execute the end-to-end RCSA lifecycle for the Personal Wealth division
• Ensure RCSA activities align with enterprise risk policies and financial-sector regulatory guidance
• Establish standardized RCSA methodologies and ensure consistent adoption across first-line teams
• Facilitate workshops with business leaders to identify and assess inherent and residual risks
• Ensure risks and controls are accurately mapped to key processes
• Develop and manage workshops evaluating internal controls supporting operations, regulatory reporting, customer interactions, and transactional processes
• Prepare RCSA summaries, dashboards, control performance metrics, and risk profiles for senior risk committees, business executives, and regulators
• Provide insights and trends on emerging risks, control weaknesses, and concentration areas
• Support risk committee meetings, compliance reviews, and exam preparation
• Advise business leaders, risk partners, compliance, internal audit, and issue management teams
• Educate front-line and control owners on RCSA requirements, regulatory expectations, and operational risk best practices
• Lead enterprise-level control initiatives across multiple business lines
• Design and implement scalable control frameworks
• Provide strategic guidance on risk identification, measurement, and mitigation
• Identify control gaps, propose solutions, and drive continuous improvement
• Build strategic partnerships and facilitate cross-functional collaboration
• Serve as a subject matter expert, mentor peers and junior specialists, and represent the function in enterprise forums and regulatory discussions
• Participate in special projects and perform other duties as assigned

Senior Specialist, Business Controls Oversight – RCSA

Security Engineer

• Help define and implement Application Security strategy and secure SDLC practices across the organization
• Partner with development teams to establish security requirements early in the software development lifecycle
• Design and implement security controls and guardrails for continuous and secure application delivery
• Develop and maintain security standards and architecture patterns for APIs, cloud-native applications, containers, serverless platforms, and emerging technologies
• Assess, prioritize, and drive remediation of application and infrastructure vulnerabilities
• Configure, integrate, and onboard teams to application security tools across CI/CD environments
• Automate security processes and controls
• Conduct security reviews, threat analysis, and risk assessments
• Identify vulnerability root causes and provide remediation guidance
• Ensure application security solutions are implemented, integrated, and delivering expected coverage
• Develop security metrics, reporting, and dashboards
• Provide secure coding guidance, technical consultation, and training
• Maintain security documentation
• Stay current with industry trends, emerging threats, and OWASP, NIST, and SANS guidance
• Support application security standards, policies, and governance initiatives

Application Security Specialist

Social Media Manager

• Design, implement, and deploy technology platforms supporting business needs
• Improve platform capabilities, performance, and effectiveness
• Provide advanced technical support and ensure reliable production environments
• Troubleshoot and resolve complex hardware and software issues across multiple platforms
• Develop technical standards and evaluate vendor products and technologies
• Recommend vendor selections and new technologies
• Promote code into development, test, and production environments
• Provide follow-up production support and submit change control requests
• Understand client business functions and determine appropriate technical tools
• Train and mentor junior staff
• Troubleshoot complex issues escalated from staff and provide guidance
• Maintain department documentation
• Administer system activities and write technical deliverables
• Perform systems analysis, requirements analysis, and logical and physical design
• Participate in special projects and perform other assigned duties

Marketing Technologist, Social Media

Data Scientist

• Lead execution of large-scale, complex analytics projects
• Apply quality control and risk assessment to models, methodologies, outputs, and processes
• Lead deep-dive diagnostic, predictive, and prescriptive analytics
• Create alternative model approaches to assess complex model design and advance future capabilities
• Mentor and develop junior data scientists and analysts
• Identify and diagnose data inconsistencies and errors
• Document data assumptions and address data gaps
• Engage senior leadership to understand business processes and develop hypotheses
• Translate business requirements into analytic approaches
• Guide test design, research design, and model validation
• Provide statistical consultation services
• Serve as analytics expert on cross-functional teams for strategic initiatives
• Prepare and deliver insight presentations and action recommendations
• Communicate complex analytical findings and implications to business leaders
• Participate in special projects and perform other assigned duties

Principal Data Scientist

• Manage a team of data scientists responsible for diagnostic, predictive, and prescriptive analytics projects
• Support the evolution and strategy of Vanguard's data science capabilities
• Oversee deep-dive analytics for Traditional AI and Generative AI projects
• Create alternative model approaches to assess complex model design and advance future capabilities
• Identify and diagnose data inconsistencies and errors; document data assumptions and fill data gaps
• Engage internal stakeholders to understand business processes and develop hypotheses
• Translate business requirements into analytic approaches
• Guide test design, research design, and model validation
• Provide statistical consultation and serve as analytics expert on cross-functional strategic initiatives
• Execute operational plans and collaborate with department or functional heads on goals
• Prepare, review, and deliver insight presentations and action recommendations
• Communicate complex analytical findings and implications to business leaders
• Design and refine data mining architectures, analytical protocols, and statistical reporting methods
• Conduct research into cutting-edge analytics methodologies
• Hire, evaluate, supervise, train, and develop crew
• Set performance standards, review performance, and make compensation decisions in accordance with HR policies

Manager, Data Science

• Lead execution of large-scale, complex analytics projects
• Apply quality control and risk assessment to models, methodologies, outputs, and processes
• Lead deep-dive diagnostic, predictive, and prescriptive analytics
• Create alternative model approaches for complex model design and future capabilities
• Mentor and develop junior data scientists and analysts
• Identify and diagnose data inconsistencies and errors
• Document data assumptions and address data gaps
• Engage with senior leadership to understand business processes and develop hypotheses
• Translate business requirements into analytic approaches
• Guide test design, research design, and model validation
• Provide statistical consultation services
• Serve as analytics expert on cross-functional teams for strategic initiatives
• Prepare and deliver insight presentations and action recommendations
• Communicate complex analytical findings and implications to business leaders
• Participate in special projects and perform other assigned duties

Data Scientist, Specialist

Machine Learning Engineer

• Define and lead technical architecture for enterprise-scale AI and ML platforms
• Design scalable, resilient, and reusable AI systems for mission-critical workloads
• Establish architectural standards, engineering patterns, and best practices for AI deployment and operations
• Drive technical decisions around model serving, inference optimization, agent architectures, orchestration frameworks, observability, and AI infrastructure
• Partner with AI researchers to transform prototypes into production-grade solutions
• Operationalize advanced AI capabilities including LLMs, Trustworthy and Responsible AI, and agentic AI systems
• Establish repeatable pathways to accelerate innovation-to-production cycles
• Solve complex AI engineering and scalability challenges
• Design systems balancing performance, latency, governance, security, and cost
• Drive adoption of MLOps, LLMOps, and AI platform engineering best practices
• Improve robustness, maintainability, observability, and operational readiness of AI products
• Identify and eliminate architectural bottlenecks affecting scale, reliability, or client experience
• Provide coaching, architecture reviews, design guidance, and technical leadership
• Own operational excellence, reliability, performance, and availability of products
• Lead response and resolution for production incidents, performance degradation, model failures, and system outages
• Serve as senior technical escalation point for challenging production issues
• Establish practices for monitoring, observability, alerting, incident management, capacity planning, and SLOs
• Mentor junior engineers in troubleshooting, root cause analysis, operational decision-making, and incident response
• Lead post-incident reviews and long-term corrective actions
• Develop operational processes that keep AI solutions secure, scalable, performant, and reliable
• Partner with product, infrastructure, security, and support teams to identify operational risks and improve service reliability
• Mentor AI and ML engineers and foster technical excellence and operational ownership
• Represent the team as a thought leader in scalable AI deployment, operational excellence, and responsible AI practices