Head of Engineering - Digital Pathology

Job Title Head of Engineering - Digital Pathology Job Description Lead the Digital Pathology R&D organization through its next phase of engineering transformation—uniting software, scanner hardware, cloud-native platforms, AI-enabled workflows, and integrated diagnostics to deliver safe, scalable, high-quality products that improve care for patients and clinicians. Your role Lead the end-to-end Digital Pathology engineering organization across software, hardware, architecture, cloud, AI, and platform engineering; develop leaders and create a high-performing, inclusive, accountable culture. Translate business strategy, product priorities, customer and clinical needs, and financial constraints into executable roadmaps, clear decision rights, and measurable outcomes.

Build a disciplined engineering operating system spanning portfolio investment, KPIs, release and risk governance, quality systems, resource allocation, and continuous improvement. Drive frequent, predictable, on-time delivery across software, hardware, cloud, AI, and integrated systems—without compromising patient safety, product quality, cybersecurity, privacy, or regulatory compliance. Lead the shift toward secure, scalable cloud-native and AI-powered platforms, including SaaS models, DevSecOps, automated testing, observability, reliability engineering, data services, MLOps, and responsible AI governance. Champion AI in both products and engineering, advancing AI-enabled pathology workflows while improving automation, documentation, testing, quality, and speed to market.

Ensure scanner innovation and hardware–software co-design remain foundational, from image acquisition and embedded software to cloud workflows, AI analysis, enterprise integration, and service operations. Own engineering investment and resource discipline, making transparent trade-offs across innovation, technical debt, quality, customer commitments, capacity, risk, and business impact. You will lead established software, hardware, and architecture leaders across teams in Best and Bangalore. You will partner closely with Product Management, Quality, Regulatory, Clinical Affairs, Service, Operations, Finance, Privacy, Cybersecurity, Legal, and commercial leaders. Across Philips, you will represent Digital Pathology in the wider Integrated Diagnostics ecosystem, collaborating with Clinical Informatics, Imaging Informatics, Enterprise Informatics, VNA, cloud, data, AI, platform, and enterprise architecture teams to advance shared capabilities and integrated workflows.

You’re the right fit if you Bring 10+ years of progressive engineering, R&D, or technology leadership experience, including leadership of large multidisciplinary engineering organizations in a regulated or mission-critical environment. Combine strong software, platform, cloud, and AI fluency with proven operating rigor—using KPIs, governance, risk management, and continuous improvement to deliver complex products predictably and at high quality. Have experience with cloud-native architecture, SaaS operating models, DevSecOps, automated testing, cybersecurity, privacy, observability, platform modernization, and software engineering best practices. Have strong understanding of AI/ML product development, MLOps, data pipelines, model lifecycle management, responsible AI, AI governance, validation, monitoring, and traceability.

Have a quality, safety, privacy, and cybersecurity champion who understands that speed only matters when paired with reliability, compliance, and customer trust. Are a change leader who can modernize technology, operating models, engineering culture, organizational capabilities, and cross-business ways of working. Have experience in medical imaging, digital pathology, diagnostics, enterprise imaging, healthcare informatics, or connected medical devices is preferred. Have experience with healthcare interoperability standards such as DICOM, DICOMweb, HL7, FHIR, IHE, LIS, PACS, VNA, or enterprise imaging workflows is preferred. Led hardware-software integrated systems, including embedded software, image acquisition, optics, sensing technologies, or complex regulated devices.

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