Digital R&D Principal Engineer

Job description

About Sanofi Sanofi is a global biopharmaceutical company dedicated to chasing the miracles of science to improve people's lives. Our Digital R&D Software Engineering team sits at the intersection of cutting-edge technology and life-changing medicine — building the digital backbone that accelerates drug discovery, clinical development, and patient outcomes. We are guided by our values: Aim Higher, Act for Patients, Be Bold, and Lead Together. Position Summary We are looking for a talented and driven AI Software Engineer – Agentic Solutions to join Sanofi's Digital R&D Software Engineering team. In this mid-level role, you will design, develop, and deploy agentic AI systems that autonomously reason, plan, and act to solve complex challenges across pharmaceutical research and development. You will work at the forefront of applied AI — building multi-agent architectures, LLM-powered workflows, and intelligent automation pipelines that directly support Sanofi's mission to bring life-saving therapies to patients faster. This includes hands-on experience with platforms such as AWS Bedrock and AWS AgentCore for scalable agent deployment, and MCP (Model Context Protocol) for standardized tool and data source integration. This is a high-impact role for an engineer who is passionate about autonomous AI systems and wants to apply them in a meaningful, regulated, and scientifically rigorous environment. Key Responsibilities &#x1f916; Agentic AI Design & Development • Design, build, and deploy autonomous AI agent systems capable of multi-step reasoning, planning, and task execution across R&D workflows • Develop multi-agent architectures where specialized agents collaborate, delegate, and coordinate to solve complex pharmaceutical problems • Implement tool-using agents that interact with APIs, databases, internal systems, and external data sources • Build feedback loops and self-correction mechanisms to improve agent reliability and accuracy over time • Leverage AWS AgentCore for agent lifecycle management, memory persistence, and tool integration — deploying and managing agents at scale in a governed, enterprise environment • Design and implement MCP (Model Context Protocol)-based agent architectures, building MCP servers and clients to standardize how agents interact with external tools, data sources, and Sanofi's internal services &#x1f9e0; LLM-Based Solution Engineering • Develop and fine-tune LLM-based applications using frameworks such as LangChain, LlamaIndex, AutoGen, CrewAI, or similar • Design and implement Retrieval-Augmented Generation (RAG) pipelines to ground agents in Sanofi's proprietary scientific and operational knowledge • Engineer prompt engineering strategies, chain-of-thought reasoning, and structured output parsing for production-grade reliability • Evaluate and benchmark LLM performance across models (GPT-4, Claude, Mistral, Llama, etc.) for specific pharmaceutical use cases • Build and deploy agentic solutions using AWS Bedrock Agents and Bedrock Knowledge Bases, leveraging foundation models available on Bedrock (e.g., Claude, Titan, Llama) for scalable, managed generative AI workloads &#x1f3d7;️ Software Engineering & Architecture • Write clean, maintainable, production-ready Python code following software engineering best practices (SOLID principles, design patterns, code reviews) • Build RESTful and event-driven APIs to expose agent capabilities to downstream applications and users • Implement CI/CD pipelines, automated testing (unit, integration, regression), and monitoring for AI systems • Ensure observability of agent behavior through logging, tracing, and evaluation frameworks (e.g., LangSmith, Arize, Weights & Biases) &#x1f517; Systems Integration • Integrate agentic solutions with Sanofi's existing digital ecosystem including data platforms, clinical systems, ERP, and knowledge management tools • Connect agents to vector databases (Pinecone, Weaviate, pgvector, Chroma) for semantic search and memory management • Work with cloud-native services ( AWS) to deploy scalable, secure, and compliant AI workloads — including AWS Bedrock managed AI services for foundation model access and agent orchestration • Integrate MCP-compatible tools into agent workflows, enabling standardized, interoperable connections between AI models and external data sources, APIs, and enterprise systems • Collaborate with data engineers to ensure agents have access to high-quality, governed data pipelines &#x1f91d; Collaboration & Delivery • Partner with product managers, data scientists, and domain experts (biologists, clinicians, regulatory specialists) to translate scientific needs into agentic AI solutions • Participate in Agile ceremonies (sprint planning, retrospectives, demos) and contribute to team velocity • Contribute to technical documentation, architecture decision records (ADRs), and internal knowledge sharing • Mentor junior engineers and contribute to the team's AI engineering standards and best practices Required Qualifications Technical Skills • Programming: Strong proficiency in Python (3.9&#43;); familiarity with async programming, type hints, and packaging • AI/ML Frameworks: Hands-on experience with LangChain, LlamaIndex, AutoGen, CrewAI, Semantic Kernel, or equivalent agentic frameworks</p