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
  • Apply industry-standard financial ontologies (e.g. FIBO) to structure and ground data
  • Design knowledge graph integrations to improve AI accuracy and compliance
  • Validate ontology completeness and accuracy for financial applications
• 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
• LLM frameworks and prompt engineering for financial applications
• 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

• Strategic business thinker who can identify valuable AI application opportunities
• 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
B2B contract, full remote, can be part-time or full-time engagement.
Time zone: Europe
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