AI Data Technical Lead - Regulatory Affairs and China Clinical Development - Pharma R&D

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 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. Driven by purpose and passion, we’re building a future where digital is a core strength across all of Roche, enabling smarter ways of working, unlocking human potential, and driving breakthroughs that truly matter for millions of patients around the world. As an AI Data Technical Lead , you will act as a seasoned engineering leader who takes end-to-end ownership, drives software excellence, and actively challenges the status quo. In this role, you will foster a culture of technical mentorship and cross-functional collaboration while designing complex, full-stack software solutions. Blending advanced GenAI engineering, enterprise integration, open-source innovation, and AWS cloud expertise, you will lead the creation of production-grade, highly secure AI agents. Specifically, you will architect and execute multi-agent orchestration systems and data transformation pipelines that convert complex regulatory datasets in a strict GxP-regulated environment. The opportunity: Agentic Architecture: Design, deploy, and scale multi-agent orchestration systems and autonomous workflows using cutting-edge frameworks. Advanced RAG Pipelines: Build and optimize advanced retrieval-augmented generation (RAG) pipelines over massive, heterogeneous datasets (structured and unstructured). State & Memory Management: Implement robust state management, short/long-term memory systems, and self-correction/reflection loops within agent networks. Evaluation & Guardrails: Create and implement robust evaluation metrics, observability pipelines, and guardrails for content quality, hallucination reduction, bias mitigation, and safety standards. Performance Optimization: Monitor and optimize AI inference cost, latency, throughput, token usage, and overall system reliability. Security & Access Control: Implement robust access controls, data encryption, user authentication, and prompt injection mitigation across all LLM workflows. Collaboration & Best Practices: Document and share reusable agent patterns, prompt libraries, and engineering components across cross-functional technical teams. End-to-End Pipeline Delivery: Independently leads the design, build, and maintenance of scalable data pipelines, managing specific data engineering projects autonomously from inception to deployment. Performance Optimization & Problem Solving: Solves complex data ingestion and processing challenges, actively optimizing data flows to enhance overall system performance and reliability. Stakeholder Alignment & Integration: Partners directly with business units and data scientists to understand data requirements, effectively bridging technical execution with non-technical business needs. Strategic Infrastructure Impact: Owns large-scale data engineering initiatives, implementing robust strategies that significantly modernize and strengthen the organization’s data infrastructure. Complex Data Integration: Manages large, intricate data ecosystems by seamlessly integrating multiple diverse data sources to ensure efficient, secure cross-platform data flows. Impact/Strategy: Acts as a technical mentor and aligns development plans with the global strategy. Gets involved in initiatives and tasks reaching outside of regular project scope, gives speeches, shares knowledge in organizational events (e.g., DevOps Days, Tech Talk), and engages in the organization of knowledge-sharing events. Who you are: Education & Experience: Bachelor’s or Master’s degree in Computer Science, Software Engineering, or related technical field (Required), along with 10+ years of professional software development experience (Required). Technical Proficiency: Strong full-stack expertise with hands-on experience in LLM frameworks, agentic architectures, and advanced RAG pipelines (Required); familiarity with cloud services and DevOps practices (Preferred). Problem Solving & Ownership: Proactive self-starter who takes ownership of complex architectural challenges, tackles technical debt, and drives end-to-end software delivery (Required). Collaboration & Mentorship: Strong communicator who enjoys mentoring peers, sharing knowledge across cross-functional teams, and bridging technical solutions with business needs (Required). Continuous Improvement: Curious mindset eager to challenge the status quo, adopt emerging AI technologies, and align development practices with global strategies (Required). Strong backend and full-stack skills in Python, R, FastAPI, and modern cloud architectures. Event-Driven & Serverless Patterns. Agentic AI and LLM skills , including Agent Frameworks (Example: Strands Agents, LangChain, LangGraph, Bedrock Agents), Prompt Engineering, RAG, Vector Stores, etc. Cloud platforms & infrastructures , including AWS, Terraform, Multi-Architecture Builds, Structured Logging, Distributed Tracing, Metrics / Monitoring, etc. Additional Qualifications: Exceptional communication and collaboration skills , with the proven ability to engage effectively with both technical audiences (like data scientists) and non-technical business stakeholders. Pharma & GxP Compliance: Extensive experience in pharma or biotech, architecting data pipelines that strictly comply with GxP frameworks (GCP/GMP/GVP), data integrity principles, and computer systems validation (CSV). Compliant Data Delivery: Proven capability to build scalable solutions within regulated R&D environments, aligning technical execution with critical Clinical, Regulatory, and Safety milestones. Workflow & Data Optimization: Skilled at identifying bottlenecks, eliminating operational silos, and optimizing fragmented workflows to ensure automated, streamlined solutions. Regulatory & Life Sciences Background: Demonstrated experience working within a GxP-regulated environment (e.g., Biotech, Pharma, or Medical Devices). Proven understanding of regulatory data standards, Regulatory Information Management (RIM) ecosystems, and electronic submission frameworks (e.g., eCTD Modules 1–5, ICH guidelines, 21 CFR Part 11) to ensure AI agent outputs are fully traceable, audit-ready, and compliant. Shift: CET Timezone #Hyderabad2026 Who we are A healthier future drives us to innovate. Together, more than 100’000 employees across the globe are dedicated to advance science, ensuring everyone has access to healthcare today and for generations to come. Our efforts result in more than 26 million people treated with our medicines and over 30 billion tests conducted using our Diagnostics products. We empower each other to explore new possibilities, foster creativity, and keep our ambitions high, so we can deliver life-changing healthcare solutions that make a global impact. Let’s build a healthier future, together. Roche is an Equal Opportunity Employer.