Business Analyst

Job Title: AI Business AnalystExperience: 4–8 Years

Employment Type: Full-Time

Location: AustraliaJob RoleWe are looking for an AI Business Analyst who can work closely with customers and business stakeholders to identify business challenges, translate them into AI-driven use cases, and partner with data scientists and engineering teams to shape solutions that actually work in practice.The role requires strong business analysis skills combined with solid conceptual knowledge of AI and Generative AI — enough to have credible, detailed conversations with technical teams and challenge what's realistic, without needing to build the solution personally.

The candidate acts as the bridge between business stakeholders, customers, and technical teams. Experience in financial services is a plus, given the domain of this engagement.Roles & ResponsibilitiesEngage with customers and business stakeholders to understand business processes, challenges, objectives, and requirements.Identify and evaluate opportunities for AI, Machine Learning, Generative AI, and automation to solve business problems.Translate business requirements into AI use cases, user stories, functional requirements, workflows, and acceptance criteria.Analyse existing business processes and identify where AI can improve productivity, accuracy, or customer experience.Partner with Data Scientists, ML Engineers, and Software Engineers to shape and refine AI solution design — asking the right questions, not writing the code.Act as the functional bridge between customers and internal engineering teams, ensuring requirements are understood correctly on both sides.Support POCs and pilots by defining success criteria, validating outputs against business intent, and gathering stakeholder feedback.Understand LLMs, RAG, AI Agents, prompt engineering, and embeddings well enough to assess whether a proposed solution will realistically meet the business need.Evaluate AI outputs for accuracy, relevance, and business suitability — flagging gaps for the technical team to address.Work with technical teams to understand APIs, data sources, and integration constraints as they affect requirements (not to build the integrations).Support data analysis and validation of business assumptions using SQL and other analytical tools.Support UAT by defining test scenarios and validating results against business requirements.Prepare and maintain BRDs, FRDs, user stories, process flows, and functional specifications.Track requirements, risks, issues, dependencies, and deliverables.Run solution demonstrations and communicate AI capabilities and outcomes to customers and stakeholders in plain business language.Stay current on emerging AI/GenAI trends and spot where they apply to real business problems.Must-Have SkillsStrong experience in Business Analysis, Technical Business Analysis, or Solution Consulting.Solid conceptual understanding of AI and Generative AI — what these systems can and can't reliably do.Working knowledge of LLMs, RAG, and AI Agent concepts (conceptual fluency, not hands-on model building).Understanding of prompt engineering and how LLM outputs are evaluated.Strong experience in requirements gathering, documentation, and stakeholder management.Ability to translate business requirements into functional requirements and AI use cases.Strong analytical and problem-solving skills.Working understanding of APIs, databases, and data flows — enough to assess feasibility and write accurate requirements.Strong communication and presentation skills, including explaining technical trade-offs to non-technical stakeholders.Experience working directly with customers/business stakeholders.Ability to work effectively with Data Scientists, ML Engineers, and Software Engineers as a peer, not a passenger.Required SkillsGenerative AI / LLM conceptsRAG and AI Agent conceptsBusiness Analysis & Requirements EngineeringSQL & Data AnalysisConceptual understanding of APIs & system integrationsAgile / ScrumUAT & Solution ValidationFunctional & Technical DocumentationGood-to-Have SkillsExposure to Python or another programming language (helps you read what's technically feasible, not required to write production code).Familiarity with OpenAI, Azure OpenAI, AWS Bedrock, Google Vertex AI, or similar platforms.Awareness of LangChain, LlamaIndex, Semantic Kernel, or similar frameworks.Basic understanding of Vector Databases and Embeddings.Experience supporting AI/GenAI POCs (as the BA, not the builder).Experience with enterprise platforms such as SAP, Salesforce, ServiceNow, CRM, or ERP systems.Awareness of AI Governance, Responsible AI, and Data Privacy considerations.Previous experience in consulting or professional services.Domain knowledge in financial services — e.g., lending, payments, wealth management, insurance, or leasing/asset finance — including familiarity with relevant compliance and regulatory considerations (KYC, AML, data privacy in finance).Key CompetenciesCustomer-centric approachStrong business acumen with credible technical fluencyExcellent analytical and problem-solving abilityAbility to work in ambiguous, fast-changing environmentsStrong stakeholder managementExcellent verbal and written communicationAbility to explain complex AI concepts in simple business termsStrong collaboration across business and technical teamsPreferred Candidate ProfileThe ideal candidate can understand a business problem, identify how AI can solve it, and translate that into requirements a technical team can build from — staying involved through validation and deployment as the business voice in the room, not as the person writing the code.Suited for candidates with experience as an AI Business Analyst, Technical Business Analyst, AI Consultant, Solution Consultant, Product Analyst, or AI Product Manager. Prior exposure to the finance domain is an added advantage but not mandatory — strong AI/BA fundamentals matter more than sector background.