AI Business Analyst / Product Manager

Job description

**This position is listed on behalf of a partner company, which manages all applications and next steps. Our partner is looking for an AI Business Analyst / Product Manager based in the United States.** We are seeking a strategic and hands-on AI professional who can identify high-value business opportunities and turn them into practical, measurable AI solutions. This role bridges business analysis, product management, and applied AI, helping organizations improve workflows, manage risks, and achieve tangible returns on investment. You will collaborate with stakeholders to define requirements, develop business cases, redesign processes, and rapidly prototype solutions using modern AI technologies. A key focus is applying generative AI and agentic systems within financial services, where governance, accuracy, and regulatory compliance are essential. You will also contribute to responsible AI implementation through structured validation, documentation, and industry-specific data frameworks. This remote consulting opportunity offers flexibility in engagement type and the chance to help move AI initiatives from early discovery to production-ready solutions. ### Accountabilities - Identify and validate AI opportunities: Facilitate stakeholder workshops to uncover, evaluate, and prioritize high-impact use cases. Develop business cases with clear return-on-investment models, success metrics, and measurable business outcomes. - Analyze and redesign business processes: Document existing workflows, identify pain points, and design improved processes with appropriate controls and boundaries for financial environments and agentic AI systems. Quantify expected operational and business improvements. - Translate business needs into technical requirements: Define solution requirements, create user stories and acceptance criteria, and establish validation methods to assess solution performance and business value. - Prototype AI-powered solutions: Build functional demonstrations using no-code and low-code tools, gather user feedback, and refine concepts. Develop prompt templates tailored to financial services applications. - Support AI governance and compliance: Design testing and validation methodologies for AI systems operating in regulated environments. Help ensure alignment with applicable frameworks and regulations, including U.S. SR 11-7 and the EU AI Act, and establish documentation practices for model risk management. - Apply financial industry ontologies: Use established financial ontologies, such as FIBO, to structure and ground data. Design knowledge graph integrations, support AI accuracy and compliance, and validate ontology completeness for financial use cases. - Maintain stakeholder alignment: Manage expectations throughout delivery, lead business reviews, communicate progress, and proactively address risks that could affect implementation or value realization. - Evaluate emerging AI technologies: Experiment with new AI capabilities, tools, and platforms to assess their practical business value and share relevant findings and recommendations with stakeholders. - Measure business impact: Track the revenue and cost impact of implemented AI solutions and monitor stakeholder satisfaction with business cases, expected outcomes, and value realization. ## Requirements - Relevant professional experience: 3–5+ years of experience in business analysis, process improvement, consulting, or a related field. - Practical AI implementation: Hands-on experience implementing large language models (LLMs) and generative AI solutions, ideally with experience taking initiatives from proof of concept into production. - No-code and low-code expertise: Experience using one or more no-code or low-code platforms to develop and demonstrate working AI solutions. - AI orchestration and technical frameworks: Hands-on experience with orchestration frameworks such as LangChain or AutoGen, and/or knowledge graph technologies. - Business analysis and requirements management: Proven ability to gather requirements, document complex processes, define project scope, and translate business needs into actionable technical specifications. - Business case development: Experience building business cases, modeling ROI, defining success metrics, and evaluating the commercial impact of technology initiatives. - Stakeholder engagement: Strong stakeholder management and workshop facilitation skills, with the ability to build consensus and maintain alignment across business and technical teams. - Financial services knowledge: Background in financial services, with an understanding of regulatory requirements and the challenges of deploying AI in regulated environments. - AI governance and validation: Familiarity with AI testing, validation, risk management, and compliance practices in regulated industries. - Financial data and ontologies: Knowledge of financial ontologies such as FIBO and graph database technologies, including Neo4j, RDF, and OWL, is valuable. - Prompt engineering: Ability to design and refine prompts and LLM workflows for financial applications and business use cases. - Strategic and analytical mindset: Ability to identify valuable AI opportunities, analyze complex workflows, and connect technical solutions to business objectives. - Communication and collaboration: Excellent communication skills, with the ability to explain technical concepts clearly to business stakeholders and translate business priorities for technical teams. - Practical, creative problem-solving: Curiosity about emerging AI capabilities, a hands-on approach to experimentation, and the ability to prototype solutions rapidly while maintaining attention to detail. - Consulting orientation: A client-focused mindset, strong relationship-building skills, and a commitment to delivering measurable outcomes. ## Benefits - Flexible engagement: B2B contract arrangement, with the option to work part-time or full-time. - Remote work: Fully remote position. - Time-zone alignment: Work aligned with the European time zone. - Compensation: Salary or contract rate was not specified in the provided job description; payment terms should be confirmed during the contracting process. - Additional benefits: Healthcare, paid leave, retirement contributions, equipment allowances, and other benefits were not specified. As this is a B2B contract, the availability of employee benefits should be clarified directly.