> Markdown version of [/jobs/ext/3933817-ai-platform-engineer](https://www.wearedevelopers.com/jobs/ext/3933817-ai-platform-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # AI Platform Engineer - **Company:** Danaher Corporation - **Location:** Indianapolis, IN, United States - **Experience:** Expert - **Salary:** $150,000.0 - $200,000.0 - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Cloud Computing, Event-Driven Programming, Laboratory Information Management Systems, Machine Learning, Search Technologies, Software Engineering, Software Systems, Enterprise Data Management, Retrieval-Augmented Generation, Large Language Models, Multi-Agent Systems, Backend, Agentic-AI, AI Platforms, Information Technology, Virtual Agents, GXP - **Published:** October 26, 2026 - **Apply:** https://www.indianapolisgigs.com/job.asp?id=3466538203&tx=KL9797FFU&pt=1&aff=0B19D771-A501-4A5E-8338-2A822B784D54&utm_source=Job%20Feed&utm_medium=textkernel&utm_campaign=DE&utm_term=0B19D771-A501-4A5E-8338-2A822B784D54 ## About the Role Are you ready to accelerate your potential and make a real difference within life sciences, diagnostics and biotechnology?, * 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 Travel, Motor Vehicle Record & Physical/Environment Requirements: * Ability to travel up to 15% domestically and internationally It would be a plus if you also possess 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 ## Description 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. In this role, you will have the opportunity to: * 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.