AI Enabled CSV Analyst

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The Digital Enablement Lead supports the Digital transformation within the Technology Quality (TQ) team. This role drives AI-enabled process improvements intelligent automation and data driven decision support across Computer Systems Validation (CSV) processes.

The Digital Enablement Lead identifies and validates high-impact use cases partners with stakeholders to translate business problems into solutions build prototypes and lead adoption through effective partnership training and governance. This position combines AI/ML software development lifecycle expertise and CSV experience with a strong ability to translate strategy into scalable solutions.

• Designs and implements practical AI-driven user cases partnering with stakeholders to translate business problems into measurable implementable AI use cases.
• Runs feasibility and impact analyses build prototypes and drive adoption through effective stakeholder enablement.
• Ensures the quality of AI-generated outputs agent behaviors and AI-assisted workflows by building benchmark scenarios defining scoring rubrics evaluating business usefulness and identifying failure patterns.
• Owns endtoend governance validation and lifecycle oversight of AI agents used across CSV processes ensuring they remain fit for intended use compliant controlled and auditable throughout deployment and operation.
• Partners with Technology Quality leaders and SMEs to define the AI roadmap maintaining a prioritized use-case catalog and aligning initiatives to business goals.
• Translates business needs into structured use cases with objectives success metrics data requirements risks controls and proposed models/techniques.
• Maintains an AI/Agent Inventory including control over Intended Use.
• Creates lightweight prototypes (scripts dashboards prompt experiments) to validate solution hypotheses and value case.
• Design and implement AI solutions for CSV processes enabling decision support and workflow automation.
• Collaborate with data Science engineering and other technology teams to define data pipelines model evaluation criteria acceptance tests and integration requirements.
• Translate business processes into product requirements user stories and acceptance criteria for data scientists ML engineers and product teams.
• Compare performance across prompt versions workflow revisions tools and models; surface evidence for release decisions and regression/improvement.
• Establish benchmark scenarios and scoring rubrics to evaluate AI outputs agent behaviors and workflows in real business contexts.
• Assess outputs for groundedness instruction adherence consistency usefulness tone control compliance and risk; identify hallucinations unsupported assertions missing logic and unsafe recommendations.
• Prepare test scripts coordinate UAT document outcomes and support validation and release documentation.
• Define prompt design strategies guardrails and explainability requirements; implement human-in-the-loop controls and risk mitigation strategies.
• Ensure all AI use cases align with J&J Responsible AI GenAI and Q&C usage guidelines
• Partner with SMEs to monitor ethical privacy and regulatory considerations for each use case (e.g. 21 CFR Part 11 GxP Annex)

Required Knowledge Skills and Abilities (Uncompromised requirements for the role):

• Bachelors or masters degree in business Data Science Statistics Computer Science or related field; or equivalent practical experience.
• 2 years in roles such as business analyst data analyst quality analyst QMS analyst or CSV lead.
• 5 years of professional experience with software development or software delivery lifecycles.
• Proven track record deploying LLMs AI agents or GenAI-powered applications in production and integrating GenAI into business workflows for measurable impact.
• Strong understanding of prompt engineering model evaluation and techniques for tuning/adaptation; familiarity with RAG and orchestration of agentic workflows.
• Data literacy: analyze datasets build reports visualize metrics; disciplined approach to data quality and lineage.
• Business analysis skills: requirements gathering process mapping writing clear specifications and supporting testing and validation.
• Effective communication critical thinking pattern recognition creative problem solving and process orientation.
• Experience evaluating outputs against nuanced criteria (beyond binary correctness) and making risk-informed decisions.
• Compliance awareness: operating in regulated environments and adherence to procedures (e.g. GxP Part 11 Annex 11).
• Experience authoring Software development documentation non-conformities Change Requests SOPs Validation Plans and Reports

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The anticipated base pay range for this position is :

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