Job Description

Job Title

Senior Imaging AI Architect

Job title:

The Senior Imaging AI Architect oversees an end-to-end data pipeline infrastructure for primarily medical imaging AI (but also Gen AI solutions and more), from data ingestion and storage through curation, feature extraction, and model training.

Your role:

Architect and own the end-to-end data pipeline

for medical imaging AI data (including related patient record data), from intake and storage through curation, feature engineering, and model training. Ensure the pipeline is scalable, secure, and optimized for large imaging datasets

while maintaining compliance with healthcare data regulations

. Additionally, architect end-to-end data pipelines for other data related to Gen AI solutions as needed.

Lead the integration of annotation tools and workflows

into the AI platform. Work with external annotation service providers and internal teams to link annotation software with our data repositories, so that images and labels flow seamlessly with full lineage and traceability.

Develop and implement data cataloging and metadata management infrastructure

in partnership with the data manager and stewards. Ensure all data assets and models are version-controlled, easily discoverable, and traceable throughout their lifecycle to support reproducibility, auditability, and regulatory compliance.

Collaborate closely with MLOps engineers and product software teams

to hand off models from R&D into production. Define clear interfaces so that once models are trained and validated in our pipeline, they can be containerized and reliably transferred into medical device software,

meeting quality and safety standards

for clinical use.

Work on a cross-functional team

of data scientists, data engineers, data ops and ML platform engineers and medical informaticians, with the software organization (including their architects & principal architect), and global Philips colleagues in a fast-paced healthcare innovation environment. You will mentor others and liaise with regulatory and quality teamsto ensure our AI solutions are safe, effective, and aligned with medical device industry standards. Constantly

stay up to date on the latest infrastructure & AI technology

that can better support production AI development and other real-world data engineering work; propose and execute on proof of concepts that lead to adoption over time. You must be able to successfully perform the following minimum Physical, Cognitive and Environmental job requirements with or without accommodation for this position .

You're the right fit if:

(4 x bullets max)

Architect and own the end-to-end data pipeline

for medical imaging AI data (including related patient record data), from intake and storage through curation, feature engineering, and model training. Ensure the pipeline is scalable, secure, and optimized for large imaging datasets

while maintaining compliance with healthcare data regulations

. Additionally, architect end-to-end data pipelines for other data related to Gen AI solutions as needed.

Lead the integration of annotation tools and workflows

into the AI platform. Work with external annotation service providers and internal teams to link annotation software with our data repositories, so that images and labels flow seamlessly with full lineage and traceability.

Develop and implement data cataloging and metadata management infrastructure

in partnership with the data manager and stewards. Ensure all data assets and models are version-controlled, easily discoverable, and traceable throughout their lifecycle to support reproducibility, auditability, and regulatory compliance.

Collaborate closely with MLOps engineers and product software teams

to hand off models from R&D into production. Define clear interfaces so that once models are trained and validated in our pipeline, they can be containerized and reliably transferred into medical device software,

meeting quality and safety standards

for clinical use.

Work on a cross-functional team

of data scientists, data engineers, data ops and ML platform engineers and medical informaticians, with the software organization (including their architects & principal architect), and global Philips colleagues in a fast-paced healthcare innovation environment. You will mentor others and liaise with regulatory and quality teamsto ensure our AI solutions are safe, effective, and aligned with medical device industry standards. Constantly

stay up to date on the latest infrastructure & AI technology

that can better support production AI development and other real-world data engineering work; propose and execute on proof of concepts that lead to adoption over time. You must be able to successfully perform the following minimum Physical, Cognitive and Environmental job requirements with or without accommodation for this position .
You're the right fit if:

You have a Bachelor's degree

in Computer Science, Biomedical Engineering, Electrical Engineering, Mathematics or a related field. (Master's or PhD preferred.)Plus,

8

+ years of experience

(or 5+ with a Master's, 3+ with PhD)

architecting large-scale data and machine learning pipelines (more weight given to recent experience and evidence of exceptional ability)

, ideally with a focus on imaging data in medical devices, healthcare, or another highly regulated industry. Demonstrated success in bringing medical devices with AI features to market using infrastructure you built and knowledge of international medical device regulations.

Proven experience in technology strategy:

you have evaluated

cloud vs. on-premises

architectures and

build vs. buy

options to meet both short-term project requirements and long-term scalability. You can point to decisions you've led in adopting the right tools and platforms for AI workflows.

Strong technical toolkit:

proficiency in distributed data processing and pipeline tools, and hands-on skills in modern AI/ML infrastructure. (We use AWS primarily--experience with cloud platforms, containerization, and MLOps frameworks will be valuable as is Python, SQL, C++.)You are also comfortable with database systems and big data tools relevant to managing image datasets as well as relational and knowledge graphs. Bonus: You are up to date on, and have built agentic orchestration solutions particularly in a production environment. Familiarity with

agile development

methodologies like SAFe

Excellent system design and problem-solving skills.

You can architect robust, scalable systems from the ground up and troubleshoot complex data flow issues. You apply a

security-first mindset.

Effective communicator and collaborator:

able to clearly

explain complex architecture decisions

to both technical teams and non-technical stakeholders. You work well in cross-functional teams and can lead through influence. A

strong data privacy and quality mindset

is in your DNA.

Passion for innovation in healthcare:

you stay updated on AI trends and are excited to apply them to improve patient outcomes.
.

How we work together

We believe that we are better together than apart. For our office-based teams, this means working in-person at least 3 days per week.


Onsite roles require full-time presence in the company's facilities.


Field roles are most effectively done outside of the company's main facilities, generally at the customers' or suppliers' locations.


Indicate if this role is an office/field/onsite role.

About Philips

We are a health technology company. We built our entire company around the belief that every human matters, and we won't stop until everybody everywhere has access to the quality healthcare that we all deserve. Do the work of your life to help the lives of others.


Learn more about our business . Discover our rich and exciting history . Learn more about our purpose .
If you're interested in this role and have many, but not all, of the experiences needed, we encourage you to apply. You may still be the right candidate for this or other opportunities at Philips. Learn more about our culture of impact with care here .
#LI-Philips