Ascendion
AI Business Analyst Manager
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Job Description
We are seeking a visionary and results-driven AI Business Analyst Manager to join our AI Center of Excellence (CoE). The ideal candidate will champion the alignment of AI with business strategy, empowering the business to realize the potential of AI to reshape strategic goals, while translating complex organizational needs into actionable AI and analytics roadmaps.
You won’t just gather requirements; you will be the architect of business intent for our next generation of Agentic Workflows. You will serve as the crucial link between business stakeholders and AI Engineers, translating ambiguous business problems into precise Agent Behavioral Specifications and defining the business ontologies and domain rules that guide autonomous agents.
You will define the logic that allows AI to reason, not just retrieve. You will report to the Head of AI-CoE.
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Key Responsibilities
- Lead the Definition of Agentic Workflows by moving beyond traditional process mapping to design intelligent, autonomous workflows. You will define the rules of engagement, decision trees, and paths that allow AI agents to act independently within safe business boundaries.
- Core Business Analysis & Requirements Gathering, lead requirements elicitation, prioritization, and management (RACI). Translate business needs into clear user stories, acceptance criteria, and functional specifications for both traditional and AI-driven features. Conduct stakeholder interviews, requirement workshops, and walkthroughs to ensure alignment.
- Drive Technical Analysis & Integration by understanding system architecture, API interactions, data flows, and integration points to support development teams with clear mapping documents and data readiness for AI models.
- Act as the primary translator to convert high-level strategic goals into precise Agent Behavioral Specifications and technical requirements.
- Maintain Documentation & Knowledge Management by preparing and maintaining comprehensive documentation including BRDs, FSDs, User Stories, Use Case Documents, and visual process flows (BPMN) while ensuring structured version control and knowledge sharing using tools like Confluence.
- Collaborate with cross-functional teams (Dev, QA, Architecture, Product) to drive backlog grooming, sprint planning, UAT support, and defect triage. Ensure end-to-end requirement traceability in Azure and proactively communicate risks, dependencies, and operational impacts.
- Drive AI product discovery by leading stakeholder workshops to identify high-impact use cases and prioritizing the roadmap from proof-of-concept to deployment based on ROI and feasibility.
- Define success criteria by creating functional evaluation datasets and defining the business KPIs used to validate Agent performance during user acceptance testing and production.
- Champion change management by helping business units redesign organizational processes to accommodate the shift from human-centric to agent-augmented operations.
- Work with Legal and Ethical AI teams to embed compliance requirements directly into the business logic of the agents, ensuring that our autonomous systems operate responsibly and transparently.
- Collaborate across the AI CoE by working closely with AI Engineers, Ethical AI Managers, and Product Owners to ensure that business rules, compliance requirements, and user needs are correctly interpreted and embedded in every AI solution.
- Mentor and guide a team of Business Analysts, fostering a culture of innovation.
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- A bachelors degree or higher in Business Administration (MBA), Information Systems, Computer Science, or a quantitative field.
- Experience in Business Analysis, Technical Product Management, or Data Strategy.
- Operational experience with Technical Analysis including system architecture understanding.
- Proficiency in Azure (DevOps) for traceability/backlog management and Confluence for structured documentation.
- Demonstrated experience in Generative AI or Agentic systems, specifically in translating business intent into structural logic, decision trees, or behavioral specifications for LLMs.
- Strong ability to define Business Domain Models and Taxonomies, you will act as the owner of the Business Language, defining the relationships between complex business concepts to ensure AI agents reason with the correct context.
- Proven ability to act as the translator between technical complexity and business value, effectively communicating AI capabilities, limitations, and risks to senior stakeholders.
- Experience defining AI Acceptance Criteria and Quality Standards, including the creation of Golden Datasets (Question/Answer pairs) to validate that model performance meets business expectations for accuracy and tone.
- Proficiency in process modeling and visualization tools to map current human workflows versus future agent-augmented workflows.
- Strong background in Agile methodologies and experience driving Change Management or digital transformation initiatives within large enterprises.
- Understanding of Prompt Engineering concepts to structure context and business constraints that effectively guide model behavior.
- Experience in highly regulated industries where explainability and auditability are critical constraints.
- Professional certifications such as CBAP (Certified Business Analysis Professional), CSPO, SAFE or recent AI strategy certifications.
- Excellent problem-solving skills, attention to detail, and the ability to communicate complex data architectures to non-technical stakeholders.
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