Data and AI Engineer - RDT Pharma R&D

Roche is a global healthcare company focused on advancing science to ensure access to healthcare and innovative treatments. The Clinical Submission Data and Content Generation & Reuse function works on transforming clinical data and regulatory submission content creation through AI-driven automation and digital platforms. The team leverages Generative AI, Agentic Workflows, Knowledge Graphs, and advanced analytics to improve clinical and regulatory operations.

• Extensive experience leading large-scale data architecture and AI/ML deployments.
• Proven leadership on high-impact enterprise data infrastructure projects and AI architecture strategy.
• Experience optimizing latency and retrieval accuracy in production RAG or agentic AI systems.
• Contributed to data governance and ensured resilience and security of data infrastructure.
• Leadership in embedding agile software engineering standards, CI/CD, and MLOps/LLMOps frameworks.

Technical Skills:

• AI/LLM stack: Graph-based multi-agent systems, RAG optimization (vector & keyword hybrid search), MCP servers, LLM evaluation frameworks.
• Data & Cloud Engineering: AWS, distributed computing, workflow orchestration, microservices, REST APIs.
• Core Engineering: Advanced programming, distributed data systems, ETL/ELT pipelines, GitLab CI/CD integration.
• Familiarity with clinical and regulatory data standards (CDISC SDTM/ADaM, FHIR, OMOP) and integration with platforms (Veeva Vault, EDMS).

Additional Qualifications:

• Ability to interface with senior leadership translating business needs into technical roadmaps.
• Proven mentoring skills and promotion of strong engineering culture.
• Strong strategic mindset influencing cross-functional architecture and technical excellence.

Scope / Content Leadership:

• Leads design and construction of large-scale data architectures.
• Oversees and mentors junior engineers.
• Designs and deploys high-performance AI systems, RAG platforms, and multi-agent workflows.
• Architects scalable distributed data systems, cloud platforms, and ETL/ELT pipelines.

Accountability/Problem Solving:

• Solves complex data engineering problems and performance issues.
• Ensures resilience, compliance, and security standards in data and AI deployments.

Stakeholder Management:

• Liaises with senior leadership on data and AI strategy.
• Guides technical teams and influences architectural decisions.
• Influences AI strategy, roadmap prioritization, and solution adoption.

Impact/Strategy:

• Defines and executes technical roadmap for data platforms and AI capabilities.
• Leads projects impacting organizational innovation and efficiency.
• Establishes software engineering standards with automated evaluation, TDD, and testing frameworks in CI/CD.

Complexity / Product Size:

• Manages enterprise-level data systems and infrastructure.
• Designs data processing frameworks, data warehouses, and data lakes.
• Works with large-scale clinical, regulatory, and enterprise datasets.

Business / Technical ability:

• Applies software engineering principles for secure, scalable AI products.
• Acts as expert in multiple programming languages and Big Data technologies.
• Understands distributed systems, cloud data platforms, ETL/ELT patterns, and data architecture.
• Balances system accuracy with latency and costs via LLM evaluation, token optimization, model distillation, and cloud FinOps.

Roche is an Equal Opportunity Employer.