Backend & AI Platform Engineer

Danaher Corporation•Indianapolis, IN

3d•$150,000 - $200,000•Onsite

About The Position

The Backend & AI Platform Engineer is responsible for creating the backend platform that powers intelligent automation across scientific workflows. By enabling AI agents to securely access data, orchestrate experiments, and integrate with complex instrument ecosystems, this role directly drives platform scalability, customer value, and the company’s ability to deliver next generation AI-enabled laboratory operations. This position reports to the Senior Manager, Software Engineering - Automation and is part of the R&D Software team located in San Jose, California and Indianapolis, Indiana.

Requirements

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, with demonstrated ability to rapidly prototype new solutions while maintaining a clear path to production quality enterprise ready implementations

Nice To Haves

Laboratory informatics platforms and standards such as LIMS, ELN, and SiLA 2, including integration with scientific instruments and laboratory workflows.
Working in regulated or compliance driven environments, including GxP, HIPAA, SOC 2, or similar frameworks

Responsibilities

Architect and develop event-driven backend services and APIs that connect 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 that coordinate planning, execution, monitoring, and recovery across heterogeneous AI agents, devices, and software systems.
Define and govern data contracts, integration standards, and observability practices to ensure reliable, secure, and resilient communication across instrument fleets and platform services.
Rapidly prototype and evaluate emerging AI and agent technologies, then mature successful solutions into production ready capabilities that meet the performance, reliability, and compliance requirements of regulated customer environments.