The Position
Job Title: Enterprise AI & Quality Insights Architect
Roche Digital Technology (RDT) is where innovation meets purpose. As a global team at the heart of Roche, we are a community of business-minded technologists committed to help shape tomorrow’s digital future of healthcare. Our mission is to power Roche through cutting-edge digital technologies, harnessing the potential of artificial intelligence, data, and scalable tech innovations.
At Roche, we offer a hybrid work model that combines flexibility with in-person collaboration. For now, we require our employees to be in our offices on average two days per week.
Join our dynamic team as an Enterprise AI & Quality Insights Architect, where you will directly shape how artificial intelligence and advanced data platforms transform quality operations across our global network. In this role, you will lead the architectural design and deployment of cutting-edge NLP, LLM, and agentic workflows within a highly regulated healthcare environment.
The opportunity:
Enterprise AI Architecture, Scaling & Strategy
- Enterprise AI Platform Management: Design, scale, and deploy robust machine learning and NLP pipelines utilizing approved enterprise data platforms, primarily focusing on Dataiku and Azure ML Studio layers.
- Agentic Framework Implementation: Evaluate and deploy advanced AI solutions. Utilize the Claude Agent SDK or comparable approved SDKs as targeted implementation options for complex use cases that genuinely require custom, automated agents to navigate cross-system data silos.
- AI Use-Case Backlog Governance: Architect and mature our global AI Use-Case Backlog. Guide the deployment of Natural Language Processing (NLP) and Large Language Models (LLMs) to automate initial sorting, risk-grading, and real-time categorization of complex quality data.
- Sustainable Data Infrastructure: Oversee the conceptual data modeling and integration pipelines feeding into core analytics repositories (such as Snowflake and AWS). Partner with builders to translate complex datasets into high-performing enterprise business intelligence views.
Strategic Product Ownership & Automated Governance
- Agile Product Architecture: Assume formal Product Owner and architectural design oversight for core Quality Insight platforms, dashboards, and automation frameworks.
- DevOps & Workflow Optimization: Establish and Champion clean repository management, version control, and collaborative code review practices via Git. Drive standardized automation workflows utilizing Jira and Confluence to optimize the subchapter's intake pipeline and eliminate communication latency.
GxP Compliance, CSV Integration & Matrix Leadership
- Computerized System Validation (CSV) Alignment: Ensure all deployed AI models, automated scripts, and data pipelines adhere to computerized system validation protocols under GxP, US FDA (21 CFR Part 820), and ISO 13485 standards. Guide the team in authoring, reviewing, and executing technical validation documentation for data integrity.
- Cross-Functional Strategy: Partner directly with Quality Site Heads, Business Leaders, and global cross-functional squads to break down organizational data silos and resolve systemic reporting barriers across site networks.
- Community of Practice: Establish, champion, and mentor an Operations Quality Community of Practice for Quality AI & Data Insight
What we offer:
- Contract Details: Employment via an external recruitment agency for a period of 18 months (Zatrudnienie przez zewnętrzną agencję na okres 18 miesięcy).
- Compensation Range: 228,900.00 PLN – 425,100.00 PLN gross annually (depending on experience and seniority level).
- Impact & Exposure: Direct exposure to enterprise-scale AI architecture, global cross-functional leadership, and cutting-edge digital health technology in a highly innovative environment.
- Work Model: Flexible hybrid working model with modern office space in Warsaw.
Required Skill Set & Competencies:
- AI & Machine Learning Architecture: Strong hands-on engineering proficiency with enterprise data science environments (such as Dataiku or ML Studio). Advanced understanding of NLP, LLMs, and prompt engineering architectures.
- Developer & Execution Tooling: Strong proficiency in core programming for data data modeling (Python, SQL) and developer workflows (Git, Jira, Confluence, and script automation environments).
- Agentic Framework Familiarity: Hands-on experience or deep conceptual understanding of custom agent architectures utilizing tools like the Claude Agent SDK or comparable enterprise-approved development kits.
- Data Systems Awareness: Solid structural knowledge of cloud data warehousing (Snowflake), pipeline concepts (AWS), and business intelligence delivery tools (ThoughtSpot, Tableau).
Background & Experience:
- Education: Bachelor's, Master's, or Ph.D. degree in Data Science, Informatics, Data Analytics, Computer Science, or a related technical field.
- Professional Experience: 5-7+ years of experience building and deploying machine learning algorithms, complex data models, or automated software tools to support enterprise-level decision-making.
- Domain & Validation Knowledge: Experience working within a highly regulated manufacturing environment (such as Pharma, Diagnostics, or Medical Devices). Sound understanding of GxP compliance, US FDA 21 CFR Part 820 Quality Management System Regulations, and ISO 13485/9001 standards. Prior experience with Computerized System Validation (CSV) protocols is highly preferred.
- Strategic Matrix Leadership: Proven capability acting as a principal technical leader, driving global cross-functional projects, and aligning stakeholder expectations with a team-first, agile mindset.
