Objective: Identify and validate high-value AI opportunities, rapidly prototype solutions, and ensure implementations deliver measurable business outcomes and tangible ROI. KPI: - Revenue/cost impact of implemented AI solutions - Stakeholders' satisfaction with business case clarity and realization Areas of Responsibility: - Lead Discovery Process and Validate AI Opportunities - Facilitate stakeholder workshops to identify and prioritize high-impact AI use cases - Develop business cases with clear ROI models and success metrics - Build consensus among stakeholders on solution direction - Map and Redesign Business Processes - Document current workflows and pain points - Design workflows with appropriate boundaries and controls for financial environments and Agentic AI systems - Quantify expected business improvements - Define AI Solution Requirements - Translate business needs into clear technical requirements - Create user stories and acceptance criteria - Establish validation approaches for measuring success - Create Solution Prototypes - Build functional demonstrations using no-code/low-code tools - Gather user feedback to refine concepts - Develop prompt templates for financial use cases - Implement AI Governance and Compliance - Develop testing methodologies for AI systems in regulated environments - Ensure alignment with financial regulations (e.g US SR 11-7, EU AI Act) - Create documentation standards for model risk management - Leverage Financial Services Industry (FSI) Ontologies - Design knowledge graph integrations to improve AI accuracy and compliance - Ensure Ongoing Business Alignment - Manage stakeholder expectations throughout delivery - Lead business review sessions - Mitigate risks to value realization - Stay Current on AI Capabilities - Actively test and experiment with emerging AI technologies firsthand - Evaluate new tools and platforms for business value - Share relevant insights with stakeholders Skills: - Stakeholder management and workshop facilitation - Business process analysis, requirements gathering, and documentation - Project scoping, ROI modeling, and business case development - Hands-on AI tool experience, including no-code/low-code platforms - Financial ontologies and graph databases (Neo4j, RDF/OWL) - AI governance, testing, and validation in regulated environments Traits: - Detail-oriented process analyst who can map complex workflows - Technically curious with practical, hands-on AI knowledge - Exceptional communicator who can translate between technical and business stakeholders - Creative problem-solver able to rapidly prototype solutions - Client-focused consultant who builds trust and drives business outcomes Experience: - 3-5 years experience in business analysis, process improvement, or consulting - Practical implementation experience with LLMs and generative AI - Hands-on experience with one or more no-code/low-code platforms - Hands-on experience with orchestration frameworks (LangChain, AutoGen) or knowledge graphs - Demonstrated success in requirements gathering and stakeholder management - Demonstrated success moving AI projects from proof-of-concept to production in regulated environments - Experience with digital transformation or technology implementation projects - Background in financial services with understanding of regulatory requirement Terms & conditions: Full remote Capacity: full-time Time zone: Europe Start date: April