Be part of something groundbreaking
We are building innovative Generative AI capabilities that will transform how we design, operate, and deliver technology solutions across the enterprise. This Senior Business Analyst will play a critical role in driving end‑to‑end solution definition, aligning business objectives with emerging AI technologies, and ensuring successful delivery through expert requirements management and project oversight.
This position blends
strategic business analysis
,
Agile program leadership
, and
an understanding of modern full‑stack and AI engineering practices
to ensure that our GenAI initiatives deliver meaningful business value.
About the Role
The Senior Business Analyst (GenAI) acts as a bridge between business stakeholders, technical teams, and AI engineering groups. The individual will lead requirements definition, process analysis, roadmap planning, and solution validation across multiple GenAI programs. This role requires strong analytical skills, structured problem‑solving, and the ability to manage complex projects within fast‑paced, cross-functional environments.
You will collaborate closely with Product Managers, Engineering, Data Science, and Enterprise Architecture to ensure solutions are designed, built, and delivered to the highest standards. Although this is not a hands-on coding role, familiarity with modern software development, cloud platforms, AI models, and full‑stack concepts is essential for partnering effectively with engineering teams.
Your Responsibilities
Strategic Project Execution (Adapted from Software Engineering + PM/SM)
Lead and support planning, coordination, and delivery of GenAI initiatives ensuring alignment with enterprise strategy.
Develop execution plans, delivery timelines, milestones, and resource forecasts.
Ensure features and capabilities are delivered on time and meet business outcome targets.
Monitor progress, manage risks, and escalate issues with recommended mitigation strategies.
Business Analysis & Requirements Leadership
Engage with multiple business units to understand objectives, pain points, data needs, and workflow impacts.
Gather, analyze, and document business requirements, challenging assumptions to ensure clarity and feasibility.
Translate business requirements into high-quality functional specifications, user stories, wireframes, and acceptance criteria.
Validate solutions against business goals, support business case development, and define measurable success criteria.
Analyze system and data interfaces, integrations, and operational impacts including Finance, Claims, and Collections data.
Support configuration of existing systems and contribute to solution design decisions.
GenAI Solution Support
Partner with engineering teams throughout the SDLC to ensure requirements are implemented accurately.
Support model-based solution ideation by aligning use cases, data availability, constraints, and compliance requirements.
Participate in design reviews, sprint planning, backlog grooming, and testing cycles.
Assess GenAI model limitations, prompting needs, UX implications, and integration touchpoints.
Coordinate user acceptance testing, training materials, and rollout plans for GenAI enabled tools.
Agile Delivery & Scrum Leadership
Facilitate Agile ceremonies (sprint planning, stand‑ups, reviews, retrospectives).
Promote Agile maturity across teams through coaching and continuous improvement.
Track performance metrics such as velocity, burndown, defect trends, and feature completion rates.
Remove impediments and support an environment of collaboration and clarity.
Cross‑Functional Collaboration
Partner with Product Owners, GenAI SMEs, Engineers, UX designers, and data teams.
Build strong relationships with stakeholders across IT and business functions.
Coordinate with external vendors when required and ensure solution alignment with architectural guidelines.
Research & Continuous Improvement
Stay current with GenAI, full-stack trends, cloud technology, and BPM platforms (e.g., PEGA).
Recommend improvements in process, workflow, and technology performance.
Evaluate new AI capabilities and identify opportunities for automation, transformation, or modernization.