AI Business Analyst / Product Manager

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.

• 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.