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

📌 AI Business Analyst / Product Manager (España)
🏢 Neurons Lab
📍 España