AI Platform Engineer

Danaher•Fremont, CA

1d•$150,000 - $200,000•Onsite

About The Position

The AI Platform Engineer is responsible for building 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, accelerates customer value delivery, and advances the company’s vision for 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, Artificial Intelligence, Machine Learning, or a related field
7+ years of professional software engineering experience, including recent hands-on experience building AI-powered products, AI platforms, agentic systems, or intelligent automation solutions
Hands-on experience building LLM-powered applications or multi-agent systems, including RAG architectures, vector search, orchestration, tool integration, context management, memory systems, and evaluation frameworks
Experience designing and implementing AI platforms and services that securely integrate enterprise data, external tools, devices, and software systems into AI-driven workflows
Strong software engineering fundamentals with demonstrated experience rapidly prototyping AI capabilities and maturing successful solutions into secure, reliable, production ready systems

Nice To Haves

Previous experience in 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 AI platform services, agent-facing APIs, and event driven backend systems that connect laboratory instruments, cloud infrastructure, and intelligent 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, evaluate, and benchmark emerging AI, agent, and LLM technologies, then mature successful solutions into production ready capabilities that meet the performance, reliability, security, and compliance requirements of regulated customer environments.