AI Business Analyst – Applied & Agentic AI Systems

At Roche you can show up as yourself, embraced for the unique qualities you bring. Our culture encourages personal expression, open dialogue, and genuine connections, where you are valued, accepted and respected for who you are, allowing you to thrive both personally and professionally. This is how we aim to prevent, stop and cure diseases and ensure everyone has access to healthcare today and for generations to come. Join Roche, where every voice matters.

The Position

About the Role

At Roche Digital Technology (RDT), we are advancing the boundaries of Applied AI. As part of our strategic initiatives, we enable high-value AI solutions (with a strong focus on Generative AI and agentic systems) through fit-for-purpose platforms, services, and applications. The Applied AI Engineering Team is tasked with building innovative AI applications, GenAI agents, and agentic foundations.

In the 2026 tech landscape, the lines between traditional disciplines have blurred. We operate in small agile teams (typically ~9 members) powered by advanced coding agents (like Claude Code) to develop and ship solutions faster than ever before (Agentic SDLC).

To support our rapid-turnaround, high-velocity engineering teams, we are seeking a highly skilled, deeply experienced IT Business Analyst. Operating in a highly regulated pharmaceutical and clinical environment (GxP), you will serve as the strategic interface between complex business priorities, regulatory compliance frameworks, and cutting-edge engineering realities. You are not a traditional analyst who merely documents requests; you are a passionate, technically literate individual contributor equipped with advanced AI skills (including prompt engineering & modern agentic workflows) and the business acumen to collaborate closely with product leaders. Furthermore, you possess strong Product Owner (PO) skills and are fully prepared to confidently act as a Proxy PO for the squad if necessary—managing the product backlog, defining sprint goals, and steering delivery timelines to align with Roche’s strategic objectives.

Core Tech Stack & Scope

This role requires a deep understanding of three core domains: AI systems, the life sciences and pharmaceutical business context, and the complexities of operating within a highly regulated environment.

The IT Business Analyst serves as the strategic bridge between complex business requirements and cutting-edge technical execution. You will take ownership of the end-to-end requirements lifecycle for AI initiatives, ensuring that all architectural designs and engineering deliverables are scalable, high-performing, and strictly compliant with global regulatory standards. By aligning technical roadmaps with strategic priorities, you will drive the delivery of robust AI solutions that provide measurable business value and maintain the highest levels of data integrity and quality assurance.

Key Responsibilities

Agile Requirements & Product Owner Support (60% Focus):

Manage the full AI project lifecycle from opportunity identification through deployment and value realization.

Translate business goals into prioritized product backlogs, Epics, and User Stories with clear acceptance criteria.

Define MVP/MMR strategies to iteratively deliver business value while managing project risks.

Act as a Proxy PO when necessary, making critical decisions on prioritization and sprint goals.

LLM Prompt Engineering & Solution Prototyping:

Design and optimize LLM prompts to ensure accurate, secure, and relevant model outputs.

Prototype agentic workflows and evaluate model responses using Python scripting and SQL data exploration.

Develop specifications for dynamic Generative UI components and RAG pipeline context mappings.

Requirements Engineering & Business Process Analysis:

Lead requirements workshops and JAD sessions to elicit business and functional specifications.

Author standard-compliant artifacts including URS, FRS, and "as-is/to-be" process maps.

Conduct gap analyses and re-engineering assessments to optimize and automate manual workflows.

GxP Compliance, Computerized System Validation (CSV) & Software Assurance (CSA):

Guide compliance-by-design strategies for AI deployments following GAMP 5, 21 CFR Part 11, and Annex 11.

Guide risk-based CSA/CSV activities, authoring risk assessments (FMEA), trace matrices, and validation reports.

Enforce strict data integrity controls (ALCOA+) and system classifications to preserve validated states.

AI Governance, Risk Management & Observability Specifications:

Ensure governance guardrails, escalation triggers, and observability requirements for agentic AI systems are applied.

Assess AI-specific risks (drift, leakage, tool misuse) and formulate TCO/ROI business cases.

Change Control, ITSM & Configuration Management:

Manage formal Change Requests (RFC) and present impact analyses to CAB/ECAB boards.

Maintain system configuration documentation and audit-readiness for internal and regulatory inspections.

Audit Readiness & Operational Support:

Act as IT SME during audits, presenting validation evidence and requirements engineering practices.

Author SOPs, manuals, and training materials to support business readiness and operational transitions.

Practical Skills Required

Experience :

8+ years of IT Business Analysis experience supporting enterprise-scale software solutions, system integrations, and business processes.

5+ years of experience in highly regulated environments, with a strong preference for the pharmaceutical, biotechnology, medical devices, or clinical healthcare sectors.

3+ years of proven experience in Agile/Scrum product delivery, with demonstrated success managing product backlogs, writing detailed User Stories, and supporting agile ceremonies.

Hands-on AI/LLM Project Experience: Experience working directly on Generative AI or machine learning projects, supporting data preparation, prompt development, or AI application testing.

Proven track record of delivering computerized system validation or software assurance under industry-standard quality guidelines and electronic records regulations.

Demonstrated experience working with cross-functional, globally distributed engineering squads (including developers, architects, QA, and validation teams).

Agentic Workflow / aSDLC Experience: Proven experience leveraging AI productivity tools and writing/coding assistants (e.g., Claude Code, ChatGPT, Codex, GitHub Copilot) daily to accelerate elicitation, business process mapping, and requirements generation within an agentic software development lifecycle.

Skills

Must-have:

Advanced Requirements Lifecycle Mastery: Expert-level proficiency in elicitation, specification, modeling, verification, and traceability.

LLM Prompt Engineering & AI Prototyping: Proficient in designing, evaluating, and refining prompts for large language models. Ability to construct robust system prompts and templates that control model outputs and behavior.

Technical & Data Literacy (Analysis & Logical Assessment): Advanced ability to analyze complex data structures, logically assess AI model outputs, and trace data lineage. Strong technical aptitude to interpret technical specifications and evaluate system behaviors, with a focus on data-driven decision-making rather than hands-on coding or scripting.

Regulatory & Quality Expertise: Deep theoretical and practical knowledge of industry-standard regulatory and quality protocols, software validation and quality assurance standards, and global guidelines for electronic records and digital signatures.

Process Modeling & Visualization: Advanced skills in process mapping, business workflow design, and data flow diagramming using tools like Microsoft Visio, Lucidchart, or BPMN engines.

Business Case & Financial Analysis: Experience conducting financial analyses, cost-benefit modeling, and calculating the total