Backend Engineer, AI Platform

• Architect and develop event-driven backend services and APIs connecting laboratory instruments, cloud infrastructure, and AI agents into a unified platform
• Design scalable data and context management solutions for LLM-powered systems, including retrieval pipelines, memory, state management, and tool integration frameworks
• Build and maintain orchestration services coordinating planning, execution, monitoring, and recovery across heterogeneous AI agents, devices, and software systems
• Define and govern data contracts, integration standards, and observability practices for reliable, secure, and resilient communication across instrument fleets and platform services
• Rapidly prototype and evaluate emerging AI and agent technologies
• Mature successful solutions into production-ready capabilities meeting performance, reliability, and compliance requirements of regulated customer environments
• Report to the Senior Manager, Software Engineering - Automation as part of the R&D Software team

• Bachelor’s or Master’s degree in Computer Science, Software Engineering, or a related technical field
• 7+ years of experience designing, building, and supporting distributed backend systems and APIs
• Proven experience developing and operating event driven architectures, microservices, and cloud native applications using platforms such as AWS, Azure, or GCP
• Hands‑on experience building LLM-powered applications or multi‑agent systems, including orchestration, tool integration, retrieval architecture, and context management
• Strong expertise in API design and scalable backend architecture
• Ability to rapidly prototype new solutions while maintaining a clear path to production quality enterprise ready implementations
• Ability to travel up to 15% domestically and internationally

Demonstrates expertise in architecting and developing event-driven backend services and APIs, with a strong focus on scalable data management solutions for LLM-powered systems. Proven ability to design and implement reliable, secure, and resilient communication standards across diverse platforms and instruments.

• Event Driven Architecture
• API Design
• Cloud Native Applications
• LLM-Powered Applications
• Microservices

• Backend Development
• Distributed Systems
• Data Management
• Orchestration Services
• Tool Integration
• Context Management
• Prototyping
• Performance Optimization
• Compliance Requirements
• Integration Standards

• Laboratory Instruments
• AI Agents
• R&D Software
• Regulated Environments

• AWS
• Azure
• GCP