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At Agilent, we inspire and support discoveries that advance the quality of life by providing trusted answers to our customers' most critical scientific and laboratory questions. The Software & Informatics Division is one of Agilent's fastest-growing businesses, and this role is pivotal in modernizing our OpenLab Suite - accelerating the next generation of scientific software that our global customers rely on every day.

We are seeking an experienced Software Modernization Enablement Lead Engineer to drive the digital transformation of our legacy systems. In this role, you will design the standardized, scalable processes and tools that accelerate developer productivity and software modernization at scale. You will pioneer the use of generative AI and autonomous AI agents to automate code translation, extract scientific algorithms and business logic, and accelerate migration to our next-generation platform - bridging traditional enterprise systems with cutting-edge software engineering.

This is an ideal opportunity for a self-starter who is innovative, passionate about delivering world-class software, and energized by a fast-paced, next-generation product development environment. You will continuously monitor industry trends and apply emerging technologies to deliver measurable value to our customers.

• Architect AI-Driven Migration Methodology: Design and execute methodologies and tooling to refactor, rearchitect, and translate legacy codebases into modern, cloud-native architectures using AI-augmented tools.

• Build Agentic AI Workflows: Develop and implement multi-agent AI workflows to automate code analysis, logic extraction, and documentation generation.

• Ensure Code Quality: Establish automated and "Human-in-the-Loop" verification frameworks so AI-generated code is secure, performant, and compliant.

• Automate Testing: Integrate AI tools to automatically generate, execute, and maintain comprehensive unit and integration test suites throughout code translation.

• Education: Bachelor's or Master's degree in Computer Science, Software Engineering, or a related technical field.

• Experience: 8+ years in software engineering, including a minimum of 3 years in AI application development and demonstrated experience in enterprise application modernization.

• AI/LLM Integration: Hands-on experience building multi-agent AI workflows for code analysis and logic extraction; composable-skills frameworks for legacy modernization; and agentic orchestration for code generation, documentation, and test synthesis.

• Legacy & Modern Languages: Deep expertise in modern languages (.NET C#, ASP.NET Core, Python, Java, Go) and strong familiarity with legacy enterprise environments (WPF, WCF, ASP, C++, C#, or mainframe architectures).

• Cloud Platforms & Infrastructure: Hands-on experience with Kubernetes, containerization, microservices, hybrid edge-to-cloud topologies, and major cloud providers (AWS, Azure). Strong conceptual command of any major cloud platform is expected at the expert level.

• CI/CD & DevOps: Advanced knowledge of automated pipelines, Infrastructure as Code (IaC), automated unit and integration test pipelines, and Human-in-the-Loop verification frameworks.

• Platforms & Data: Familiarity with both Windows and Linux environments and database technologies.

• Communication & Collaboration: Excellent communication skills with the ability to evaluate solutions through both short-term and long-term lenses in an iterative development cycle, and a track record of working effectively across diverse, cross-functional teams.