Senior AI Engineer

Beckman Coulter Diagnostics · Bangalore

Source and collection record

Last observed by our collector: 8 October 2026 at 11:10 pm IST. This is not a manual review or a confirmation from the employer.

Employer requisition: R1319119

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Collected role description

In DHR Enterprise AI Solutions, you will be responsible for designing, developing and deploying production-grade AI solutions that create measurable business value across Danaher operating companies. You will work within multidisciplinary engineering teams to transform business opportunities into scalable AI applications, agents, services and reusable capabilities that can be adopted, operated and supported across the enterprise. Design, develop and deploy AI solutions for enterprise applications and products, building scalable AI services, workflows and reusable capabilities that solve real business problems. Develop and optimise Large Language Model (LLM) applications using prompt engineering, Retrieval-Augmented Generation (RAG), fine-tuning, agentic workflows and modern AI engineering techniques. Implement and support MLOps, DataOps and LLMOps practices for model lifecycle management, deployment, monitoring, governance and continuous improvement. Contribute to the design and implementation of scalable, reliable and maintainable AI architectures, ensuring solutions meet enterprise standards for quality, performance, security and supportability. Collaborate closely with Product Owners, Architects, AI Scientists, Platform and Data Engineering teams to build, industrialise and scale trusted, reusable AI solutions across Danaher. 5+ years of software engineering experience with significant hands-on experience building AI, machine learning or advanced analytics solutions. Strong proficiency in Python and modern AI development frameworks, libraries and tooling. Experience developing, deploying and supporting production-grade AI, machine learning or data-driven solutions in cloud environments. Strong understanding of software engineering practices, architecture patterns, APIs, microservices, CI/CD and cloud-native development. Good understanding of modern AI methodologies, including LLMs, semantic models, knowledge and context graphs, Retrieval-Augmented Generation (RAG) and agentic AI architectures. Building or deploying AI solutions in regulated industries such as life sciences, diagnostics, healthcare or advanced manufacturing. Developing AI capabilities that support knowledge extraction, decision support, process optimisation or workflow automation across enterprise data ecosystems. Enterprise AI governance and Responsible AI practices, including model evaluation, explainability, bias assessment and compliance with emerging AI regulations and frameworks. It would be a plus if you also possess previous experience in.

Collected experience requirement

5+ years