Technology Product Owner – Digital Pathology

Jobtailor; California (MO); On-site; USD 150,000 - 190,000; Full time

Job summary

Jobtailor is seeking an experienced AI Product Lead to define and advance an AI-enabled digital pathology platform. You will translate scientific use cases into practical capabilities for image analytics, multimodal models, automation, and human-in-the-loop decisions.

You will collaborate with data scientists and ML engineers to prepare data for model development, validate algorithms, and ensure scalable, compliant workflows across scanners and storage systems.

Qualifications

• Bachelor’s degree in Computer Science, Bioinformatics, Biomedical Engineering, Computational Biology, or related field.
• 5+ years of hands-on technical experience supporting scientific research platforms.
• Ideally 2–3 years focused on digital pathology, histology imaging, or biomedical imaging systems.
• Track record leading technical programs or major products end-to-end in a complex organization.
• Familiarity with whole-slide imaging formats including SVS, NDPI, and OME-TIFF.
• Experience with OpenSlide, QuPath, ImageJ/Fiji, or similar tools.
• Strong software and data engineering skills using Python/R, SQL, REST APIs, Docker, CI/CD, and AWS/Azure/GCP.
• Experience integrating slide scanners and microscopes with IT systems via APIs, vendor SDKs, or middleware.
• Understanding of SQL and/or NoSQL databases and metadata management.
• Strong troubleshooting and root-cause analysis skills for distributed systems and imaging hardware/software.
• Excellent written and verbal communication skills.
• Strong AI fluency, including assessment of foundation models, computer vision methods, and AI development tools.
• Ability to work directly with scientists in lab settings and translate needs into technical requirements.
• Preferred: Advanced degree (MS/PhD) in a related discipline.
• Preferred: TensorFlow or PyTorch, image preprocessing, large-image data pipelines, etc.

Responsibilities

• Define and maintain an AI-enabled digital pathology product strategy and roadmap.
• Translate scientific use cases into prioritized capabilities across image analytics, multimodal models, generative AI, workflow automation, and human-in-the-loop decision support.
• Evaluate and apply enterprise-approved large language models and AI assistants to accelerate requirements analysis, documentation, coding, scientific knowledge retrieval, and workflow automation.
• Build and maintain image processing pipelines, automation scripts, APIs, and integrations between scanners, viewers, storage, and analytics systems.
• Collaborate with data scientists and ML engineers to provision and optimize datasets for algorithm development and validation.
• Support annotation workflows and tool integration.
• Lead adoption of AI-enabled capabilities through pilot criteria, user feedback loops, adoption plans, and outcome metrics.
• Ensure compliance with data security, privacy, intellectual property, regulatory, and responsible AI requirements.
• Coordinate cross-functional stakeholders, vendors, and engineering teams.
• Enable scientists to acquire, access, analyze, and interpret high-quality slides and imaging data reliably and at scale.

Skills

Python

R

SQL

REST APIs

Docker

CI/CD

AWS

Azure

GCP

AI fluency

Troubleshooting

Education

Bachelor’s degree in Computer Science, Bioinformatics, Biomedical Engineering, Computational Biology, or related field

MS/PhD preferred

Tools

OpenSlide

QuPath

ImageJ/Fiji

Job description

• Define and maintain an AI-enabled digital pathology product strategy and roadmap
• Translate scientific use cases into prioritized capabilities across image analytics, multimodal models, generative AI, workflow automation, and human-in-the-loop decision support
• Evaluate and apply enterprise-approved large language models and AI assistants to accelerate requirements analysis, documentation, coding, scientific knowledge retrieval, and workflow automation
• Build and maintain image processing pipelines, automation scripts, APIs, and integrations between scanners, viewers, storage, and analytics systems
• Collaborate with data scientists and ML engineers to provision and optimize datasets for algorithm development and validation
• Support annotation workflows and tool integration
• Lead adoption of AI-enabled capabilities through pilot criteria, user feedback loops, adoption plans, and outcome metrics
• Ensure compliance with data security, privacy, intellectual property, regulatory, and responsible AI requirements
• Coordinate cross-functional stakeholders, vendors, and engineering teams
• Enable scientists to acquire, access, analyze, and interpret high-quality slides and imaging data reliably and at scale

Requirements

• Bachelor’s degree in Computer Science, Bioinformatics, Biomedical Engineering, Computational Biology, or related field
• 5+ years of hands-on technical experience supporting scientific research platforms
• Ideally 2–3 years focused on digital pathology, histology imaging, or biomedical imaging systems
• Track record leading technical programs or major products end-to-end in a complex organization
• Familiarity with whole-slide imaging formats including SVS, NDPI, and OME-TIFF
• Experience with OpenSlide, QuPath, ImageJ/Fiji, or similar tools
• Strong software and data engineering skills using Python/R, SQL, REST APIs, Docker, CI/CD, and AWS/Azure/GCP
• Experience integrating slide scanners and microscopes with IT systems via APIs, vendor SDKs, or middleware
• Understanding of SQL and/or NoSQL databases and metadata management
• Strong troubleshooting and root-cause analysis skills for distributed systems and imaging hardware/software
• Excellent written and verbal communication skills
• Strong AI fluency, including assessment of foundation models, computer vision methods, and AI development tools
• Ability to work directly with scientists in lab settings and translate needs into technical requirements
• Preferred: Advanced degree (MS/PhD) in a related discipline
• Preferred: Experience with TensorFlow or PyTorch, image preprocessing, large-image data pipelines, object storage, scanner ecosystems, viewer platforms, MLOps, LIMS, compliance frameworks, annotation workflows, and pharmaceutical, biotech, or academic core facility environments

Core Competencies

Demonstrates expertise in AI-enabled digital pathology product strategy, including image analytics, multimodal models, and workflow automation. Proficient in integrating scientific use cases with technical requirements while ensuring compliance with data security and regulatory standards.