Senior Engineer, Applied AI & Engineering Platforms
Core
Architect, build, and operate production-grade multi-agent systems and AI foundations layer to accelerate drug discovery and streamline clinical/regulatory operations in a GxP-regulated environment.
Role type
Senior IC Applied AI & Engineering Platforms Engineer
Builds
Production-grade multi-agent systems, AI foundations layer (LLM gateway, vector stores, RAG pipelines), and engineering standards for agentic workflows.
Domain
Life Sciences / Pharmaceutical / Generative AI / Agentic Systems
Deliverable
production ML models
Required skills
Python (async, RESTful API), Multi-agent system architecture, RAG pipeline development, Cloud AI platforms (AWS/Azure/GCP), Prompt engineering, System design for distributed AI, GxP compliance knowledge
Preferred skills
LLMOps/AIOps tooling, Agent evaluation frameworks, MCP/A2A standards, TypeScript/Go, Pharmaceutical industry experience, Kubernetes/Docker
Technologies
LangChain, LangGraph, CrewAI, OpenAI Agents SDK, AutoGen, Semantic Kernel, FastAPI, pgvector, Pinecone, Azure AI Search, LlamaIndex, AWS Bedrock, Azure AI Foundry, Google Vertex AI, LangSmith, Langfuse, MLflow, Salesforce, Veeva, SAP, ServiceNow, Databricks, MuleSoft, PyTorch, Hugging Face
Responsibilities
Architect and own production-grade multi-agent systems using orchestration frameworks; Design and maintain shared AI infrastructure including LLM gateways and RAG pipelines; Define end-to-end SDLC for agentic systems with automated evaluation gates; Implement full-stack observability and production reliability controls; Design agent authorization models and governance controls for GxP compliance; Partner with cross-functional teams to translate pharmaceutical problems into agent system designs.
Seniority
Senior, hands-on IC
