Principal AI Engineer

Role overview

Principal AI Engineer at Beckman Coulter Diagnostics

Responsibilities

• Design and scale intelligent solutions that accelerate software development, code and test generation, verification and validation, defect investigation, technical data analysis, and repetitive engineering work.

Required qualifications

• if applicable for role.
• Must have a valid driver’s license with an acceptable driving record.

Preferred qualifications and skills

• It would be a plus if you also possess previous experience in.

Employment details

• Location: Bangalore [Karnātaka] [India]

About the employer

• The Principal AI Engineer – R&D is a senior individual-contributor technology leader responsible for defining the architecture, engineering standards, and technical direction for enterprise AI solutions that transform research and development across Beckman Coulter Diagnostics.

Benefits

• Bachelor’s degree in computer science, Software Engineering, Computer Engineering, Data Science, Artificial Intelligence, or related technical discipline. 14+years of experience developing enterprise software solutions using Python, C#, Java, or similar languages in medical device industry.

Additional role details

• This role combines hands-on solution design and development with cross-functional technical leadership to build, validate, and scale production-grade AI agents, Retrieval-Augmented Generation solutions, and intelligent engineering workflows across product development, systems engineering, software engineering, verification and validation, quality, and regulatory activities.
• The Principal AI Engineer partners with R&D and technology leaders to identify high-value opportunities, establish reusable architecture patterns and responsible AI controls, mentor engineering teams, and deliver secure, observable, compliant solutions that improve productivity, product quality, traceability, and speed to market.
• Architect and deliver production-grade AI agents, engineering assistants, and agentic workflows that improve requirements development, systems engineering, risk management, design reviews, technical documentation, and end-to-end traceability.
• Develop secure and scalable Retrieval-Augmented Generation (RAG) solutions grounded in engineering documentation, standards, technical reports, design history files, and lessons learned.
• Own the technical direction for agent architecture, orchestration frameworks, model selection and evaluation, reusable design patterns, enterprise integration, and standards for AI governance, validation, security, observability, model risk management, and responsible AI.
• Partner with R&D, quality, regulatory, security, and technology teams to prioritize high-value use cases, lead technical reviews, mentor engineers, and scale solutions that deliver measurable improvements in productivity, product quality, traceability, and speed to market.
• Experience building AI applications utilizing LLMs, agent frameworks, RAG architectures, vector databases, and cloud AI services (Azure AI, OpenAI, Anthropic, or equivalent). 25% Ability to travel domestic and international.
• Ability to lift, move or carry equipment up to 25lb, any other physical requirements.
• Medical devices, diagnostics, healthcare, biotechnology, or other regulated industries.
• Model-Based Systems Engineering (MBSE), requirements management, risk management, or engineering lifecycle tools.
• Learn about the Danaher Business System which makes everything possible.
• Travel, Motor Vehicle Record & Physical/Environment