R&D Software Architect

Job Description

Agilent’s ACG R&D organization is seeking a Software Architect to help define and evolve enterprise software platforms that support service operations and customer-facing analytics solutions. This role focuses on architecture, technical leadership, and cross‑functional collaboration.

You will work in a globally distributed, fully remote team building SaaS platforms, analytics, and monitoring solutions that integrate laboratory instruments, customer environments, and Agilent enterprise systems.

Key Responsibilities

• Define and evolve software architecture for large‑scale SaaS, analytics, and monitoring platforms.

• Translate product and business concepts into feasible technical solutions through requirements, architecture design, and proof‑of‑concepts.

• Partner with product, marketing, engineering, and leadership to align solutions with business goals.

• Architect event‑driven, data‑centric, and enterprise‑integrated systems.

• Evaluate emerging technologies, including AI‑enabled capabilities, and guide technical adoption.

• Provide architectural guidance, documentation, and technical direction to development teams.

• Clearly communicate architectural concepts to technical and non‑technical stakeholders.

• Ensure solutions are scalable, performant, maintainable, and meet regulatory requirements (ISO, GDPR, EU CRA, etc) and follow best practices in cybersecurity.

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Software Engineering, or related field.

• 8+ years of professional software development experience, including senior or architectural responsibilities.

• Hands‑on software development background with the ability to guide engineering teams (this role is not primarily coding‑focused).

• Experience designing enterprise or B2B cloud platforms, including SaaS, data/analytics, or monitoring systems.

• Strong understanding of data-centric architectures, including batch/streaming pipelines, data models, and integration patterns.

• Strong knowledge of cloud-native architectures, microservices, APIs, web app frameworks, containerization, and DevOps practices.

• Excellent communication and stakeholder engagement skills with both technical and non-technical groups.

Preferred Experience

• Experience in life sciences, laboratory informatics, scientific instruments or other regulated enterprise environments.

• Designing analytics or data platforms, including lakehouse architectures, real-time streaming, metadata management, or monitoring/observability systems.

• Familiarity with AI/ML concepts, MLOps processes, data governance, and model lifecycle considerations.

• Experience with IoT/edge architectures, telemetry ingestion, digital twins, or instrument fleet management.

• Experience with agile development methodologies and distributed team collaboration.

Additional Details

Travel Required:

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