Digital R&D Principal Engineer
Core
Design, develop, and deploy autonomous agentic AI systems that reason, plan, and act to solve complex challenges in pharmaceutical research and development.
Role type
Mid-level AI Software Engineer (Agentic Solutions)
Builds
Multi-agent architectures, LLM-powered workflows, and intelligent automation pipelines for drug discovery and clinical development.
Domain
Biopharmaceutical R&D / Applied AI
Deliverable
production ML models
Required skills
Python (3.9+), agentic frameworks (LangChain, LlamaIndex, AutoGen, CrewAI), AWS Bedrock, AWS AgentCore, Model Context Protocol (MCP), RAG pipelines, vector databases (Pinecone, Weaviate, pgvector), REST APIs, Docker, Kubernetes, SQL, Git.
Preferred skills
GxP compliance, knowledge graphs/ontologies, fine-tuning/RLHF, multi-modal AI, clinical data standards (CDISC, HL7 FHIR).
Technologies
AWS Bedrock, AWS AgentCore, LangChain, LlamaIndex, AutoGen, CrewAI, Semantic Kernel, Pinecone, Weaviate, pgvector, Chroma, Qdrant, LangSmith, Arize, W&B, GitHub Actions.
Responsibilities
Design and deploy autonomous AI agents with multi-step reasoning and tool use; build multi-agent collaboration architectures; implement RAG pipelines for proprietary scientific knowledge; develop production-grade Python code with CI/CD and observability; integrate agents with enterprise data platforms and clinical systems; mentor junior engineers and contribute to AI engineering standards.
Seniority
Mid-level, hands-on IC
