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

Overview

Lead the design and delivery of production-grade GenAI and agentic AI systems and data pipelines within Roche Digital Technology, including regulatory data pipelines in a strict GxP-regulated environment.

What you'll do

• Design, deploy and scale multi-agent orchestration systems and autonomous workflows using cutting-edge frameworks.
• Build and optimize advanced retrieval-augmented generation (RAG) pipelines over massive, heterogeneous structured and unstructured datasets.
• Implement state management, short- and long-term memory systems, and self-correction/reflection loops within agent networks.
• Create and implement evaluation metrics, observability pipelines and guardrails for content quality, hallucination reduction, bias mitigation and safety standards.
• Monitor and optimize AI inference cost, latency, throughput, token usage and overall system reliability.
• Implement access controls, data encryption, user authentication and prompt injection mitigation across all LLM workflows.
• Document and share reusable agent patterns, prompt libraries and engineering components across cross-functional technical teams.
• Independently lead the design, build and maintenance of scalable data pipelines, managing data engineering projects from inception to deployment.
• Solve complex data ingestion and processing challenges and optimize data flows to enhance system performance and reliability.
• Partner directly with business units and data scientists to understand data requirements and bridge technical execution with business needs.
• Own large-scale data engineering initiatives that modernize and strengthen the organization's data infrastructure.
• Manage large, intricate data ecosystems by integrating multiple diverse data sources to ensure efficient, secure cross-platform data flows.
• Act as a technical mentor, align development plans with the global strategy, take on initiatives beyond regular project scope, give speeches, share knowledge at organizational events (e.g., DevOps Days, Tech Talk) and help organize knowledge-sharing events.

What you'll need

• Bachelor's or Master's degree in Computer Science, Software Engineering, or a related technical field.
• 10+ years of professional software development experience.
• Strong full-stack expertise with hands-on experience in LLM frameworks, agentic architectures and advanced RAG pipelines.
• Proactive self-starter who takes ownership of complex architectural challenges, tackles technical debt and drives end-to-end software delivery.
• Strong communicator who enjoys mentoring peers, sharing knowledge across cross-functional teams and bridging technical solutions with business needs.
• Curious mindset eager to challenge the status quo, adopt emerging AI technologies and align development practices with global strategies.
• Strong backend and full-stack skills in Python, R, FastAPI and modern cloud architectures.
• Event-driven and serverless patterns.
• Agentic AI and LLM skills, including agent frameworks (e.g., Strands Agents, LangChain, LangGraph, Bedrock Agents), prompt engineering, RAG and vector stores.
• Cloud platforms and infrastructure, including AWS, Terraform, multi-architecture builds, structured logging, distributed tracing and metrics/monitoring.
• Exceptional communication and collaboration skills, with the ability to engage both technical audiences (such as data scientists) and non-technical business stakeholders.
• Extensive experience in pharma or biotech architecting data pipelines that comply with GxP frameworks (GCP/GMP/GVP), data integrity principles and computer systems validation (CSV).
• Proven capability to build scalable solutions within regulated R&D environments, aligning technical execution with Clinical, Regulatory and Safety milestones.
• Skilled at identifying bottlenecks, eliminating operational silos and optimizing fragmented workflows into automated, streamlined solutions.
• Demonstrated experience in 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), ensuring AI agent outputs are traceable, audit-ready and compliant.

Nice to have

• Familiarity with cloud services and DevOps practices.

Details

• Location: Hyderabad.
• Shift: CET timezone.