R&D Software Architect
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Job Description
Software Architect focusing on SaaS platforms and customer-facing analytics solutions at Agilent. Collaborates globally to evolve software architecture and integrate systems.
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.
Requirements:
- 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.
- 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.
Benefits:
- eligibility for bonus
- stock
- benefits
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