AI Business Analyst

Overview Our Digital Technology Team is seeking an experienced Senior AI Business Analyst with deep expertise in agile delivery, AI-driven project execution, and technology‑focused business partnership. This individual will play a key role in shaping, guiding, and delivering large‑scale AI initiatives—while also navigating traditional SDLC workflows when appropriate. The ideal candidate has hands-on experience bringing AI solutions from concept to production and thrives in a fast‑paced digital environment. Key Responsibilities AI Program & Project Leadership • Lead business analysis activities for AI-enabled initiatives, guiding work from ideation through discovery, model considerations, development, testing, and production implementation. • Partner with data scientists and engineering teams to translate business opportunities into structured use cases, user stories, workflows, and acceptance criteria. • Support operational readiness including model integration, monitoring, data validation, and performance reporting. Full SDLC & Agile Execution • Navigate all phases of the SDLC—with and without AI components—ensuring clarity of requirements, sprint alignment, quality assurance, and deployment readiness. • Drive backlog creation and grooming and assist in sprint planning and iterative delivery in a high-velocity agile environment. • Maintain reporting and project metrics to track progress, dependencies, and business outcomes. Business & Stakeholder Engagement • Work directly with business partners to shape early concepts into well‑defined functional and technical requirements. • Influence decision‑making by helping stakeholders understand how best to leverage available AI tools, data assets, and technical capabilities. • Confidently present ideas, prototypes, feasibility assessments, and solution recommendations to business leadership and cross‑functional partners. • Facilitate workshops, discovery sessions, and demonstrations to ensure alignment on goals and outcomes. Data, Analytics & Technical Familiarity • Use working knowledge of SQL, SAP, AWS (Redshift, Bedrock, etc.), and Google Analytics to identify source data, validate data requirements, and support analytical needs for AI and traditional digital projects. • Collaborate with technical teams to ensure data readiness, proper integration points, and alignment of data sources with solution needs. Emerging Tech & Vibe Coding • Apply prior experience with vibe coding to rapidly prototype, iterate, and validate concepts in collaboration with technical teams. • Serve as a champion and mentor for the technical team on vibe coding best practices, standards, and patterns to improve speed, consistency, and quality of prototype and app development. • Stay current on emerging AI capabilities, digital patterns, and platform advancements to help inform future opportunities. Qualifications Required • 5+ years of experience as a Business Analyst within digital, technology, AI/ML, or data-focused teams. • Proven experience leading or supporting large-scale AI projects through full project life cycle into production. • Strong understanding of both AI-enhanced SDLC frameworks and standard SDLC/agile practices. • Demonstrated success working with high‑velocity technology teams in fast-paced digital environments. • Strong communication and facilitation skills, with the ability to translate complex concepts into actionable business requirements. • Practical experience engaging business partners, influencing decisions, and presenting technical ideas in a clear, compelling manner. • Working familiarity with SQL, SAP, AWS (Redshift, Bedrock), and Google Analytics. • Hands-on experience developing or collaborating on vibe-coded applications. Preferred • Experience supporting solutions involving LLMs, RAG workflows, MCP, automation, or machine learning models. • Background with cloud data platforms, digital ecosystems, and modern architectural patterns. • Prior experience in digital strategy, innovation, or analytics-driven product development. • Experience with prompt engineering, including crafting, optimizing, and evaluating prompts for LLM-driven or generative AI solutions.