Lead Integration Engineer

Role overview

Lead Integration Engineer at Beckman Coulter Diagnostics

In DHR Enterprise AI Solutions, you will be responsible for designing and implementing secure, reusable integration patterns and services that connect AI solutions with Danaher data, applications, instruments and business workflows.

Responsibilities

• Design framworks for and lead integration of production-grade AI solutions into our operating companies and their software and infrastructure environments to scale the business impact of AI at Danaher.

Preferred qualifications and skills

• It Would Be a Plus If You Also Possess Previous Experience In.

Employment details

• Location: Bangalore [Karnātaka] [India]

Application details

• Collaborate with business stakeholders, architecture, engineering, platform, data and security teams, and application owners to gather requirements and enable reliable, secure, and scalable integration of AI solutions.
• Bachelor's or master’s degree in computer science, Engineering, Information Systems, or a related technical field. 8+ years of experience in enterprise application integration, software engineering, middleware development, or platform engineering.

Additional role details

• Define and implement scalable API, event-driven, and data integration architectures that enable enterprise-wide adoption of AI solutions and products and physical AI.
• Design and develop reusable integration frameworks, connectors, MCP integrations, and AI-accessible services that allow AI agents and applications to securely interact with enterprise systems (software and instruments).
• Provide technical leadership and mentorship while establishing integration standards, governance practices, and best practices that accelerate deployment of AI solutions across multiple business functions and operating companies.
• Strong expertise in API design and development, RESTful services, event-driven architectures, microservices, API gateways, and authentication mechanisms.
• Hands-on experience integrating hardware and enterprise platforms such as Salesforce, ServiceNow, SAP, Snowflake, Microsoft technologies, or other business-critical applications and data systems.
• Strong programming skills in Python, Java, C#, or similar languages, combined with experience architecting and deploying solutions on cloud platforms such as Azure, AWS.
• Building integrations for Generative AI applications, AI agents, Copilot solutions, LLM-based applications, RAG architectures, and MCP-based integrations.
• Developing AI-powered business applications using Azure OpenAI, AWS Bedrock, LangChain, Microsoft Copilot Studio, or similar AI frameworks and platforms.
• Domain knowledge and hands-on experience working with enterprise business functions and systems such as Salesforce (SFDC), Customer Relationship Management (CRM), Supply Chain, Customer Service, Commercial Operations, ERP, Order Management, or Service Management platforms.