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Health Ai Jobs (NOW HIRING)

As an AI Engineer, you'll work at the intersection of engineering and real-world business context as a builder, problem-solver, and strategic partner. You'll embed with users across Voloridge Health ...

As an AI Engineer, you'll work at the intersection of engineering and real-world business context as a builder, problem-solver, and strategic partner. You'll embed with users across Voloridge Health ...

Researcher, Health AI

San Francisco, CA · On-site

$295K - $445K/yr

Our Health AI team is focused on enabling universal access to high-quality medical information. We work at the intersection of AI safety research and healthcare applications, aiming to create ...

As an AI Engineer, you'll work at the intersection of engineering and real-world business context as a builder, problem-solver, and strategic partner. You'll embed with users across Voloridge Health ...

The brand positions itself against the legacy healthcare system and insurance industry with a fast ... Set the bar for editorial quality, pace, and aesthetic across all the company's AI content * Work ...

Growth Lead - Lotus Health AI • San Francisco, CA Lotus Health AI is infinite care. We're building the AI primary care doctor, backed by Kleiner Perkins and CRV, and we're looking for someone who ...

Content Director - Lotus Health AI • San Francisco, CA (On-site) Lotus Health AI is on a mission to make world-class primary care accessible to everyone. We combine AI with real physicians to give ...

Our Health AI team focuses on expanding access to high-quality medical expertise and aims to set a high standard for deploying AI responsibly in high-stakes domains. Improving health will be one of ...

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Showing results 1-20

Health Ai information

See salary details

$34.5K

$106K

$191.5K

How much do health ai jobs pay per year?

As of Jun 8, 2026, the average yearly pay for health ai in the United States is $105,973.00, according to ZipRecruiter salary data. Most workers in this role earn between $70,500.00 and $141,000.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive in the Health Ai position, and why are they important?

To excel in a Health AI role, you need a robust background in data science, machine learning, and healthcare informatics, typically supported by a degree in computer science or a related health or engineering field. Familiarity with tools such as Python, TensorFlow, clinical databases, and experience with HIPAA regulations and medical device standards are highly valued. Strong analytical reasoning, communication, and interdisciplinary collaboration skills help bridge the gap between technical and clinical teams. These competencies are crucial for developing effective AI solutions that improve healthcare outcomes while maintaining patient privacy and regulatory compliance.

What is a Health AI job?

A Health AI job involves developing and applying artificial intelligence technologies to healthcare. Professionals in this field work on tasks such as medical data analysis, predictive modeling, and AI-powered diagnostics. They collaborate with doctors, researchers, and tech teams to improve patient outcomes and streamline healthcare processes. Roles may include AI engineers, data scientists, or clinical AI specialists, depending on the specific focus area.

What are the common day-to-day responsibilities for someone working in Health AI?

Professionals in Health AI are often involved in designing, developing, and validating machine learning models to solve complex healthcare challenges, such as disease prediction, patient outcome analysis, or workflow optimization. You might work closely with clinicians, data engineers, and regulatory specialists to collect and preprocess medical data, ensure models are clinically relevant, and meet strict privacy standards. Additionally, you'll present findings, monitor AI system performance in clinical settings, and continuously update algorithms to reflect the latest research and datasets. The role is highly collaborative and impactful, offering a dynamic work environment at the intersection of technology and healthcare innovation.

What cities are hiring for Health Ai jobs? Cities with the most Health Ai job openings:
What are the most commonly searched types of Health Ai jobs? The most popular types of Health Ai jobs are:
What states have the most Health Ai jobs? States with the most job openings for Health Ai jobs include:
Infographic showing various Health Ai job openings in the United States as of May 2026, with employment types broken down into 1% As Needed, 75% Full Time, 18% Part Time, and 6% Contract. Highlights an 96% Physical, 1% Hybrid, and 3% Remote job distribution, with an average salary of $105,973 per year, or $50.9 per hour.
Product Manager, Health AI

Product Manager, Health AI

Gateway Recruiting

Boston, MA

Full-time

Posted 19 days ago


Job description

About the role:

The Product Manager, Health AI will drive strategy execution and delivery for a portfolio of Health AI initiatives. This role will translate clinical and business needs into well-governed programs, align stakeholders across divisions, and manage external partners and vendors to deliver measurable value. In this role, the Product Manager will work closely with AI Engineering, Platform teams, Enterprise Architecture, Data and AI Governance stakeholders, and Business Units to ensure solutions are feasible, integrated with enterprise standards, validated for clinical and technical performance, and ready for scaled adoption.

Responsibilities will include:

  • Deliver cross-divisional Health AI initiatives with clinical, R&D, and operational stakeholders by translating needs into well-defined programs, platform-enabled capabilities, and release plans with clear milestones, dependencies, and success criteria.
  • Facilitate end-to-end roadmaps and execution by establishing phase gates from discovery through pilot, validation, launch, and scale, ensuring readiness across clinical, technical, financial, and operational dimensions.
  • Establish and manage enterprise Health AI preferred partnerships and vendor ecosystems that divisions can leverage to accelerate solution development and deployment, driving cost sharing, standardized onboarding, enterprise agreements, and reusable integrations.
  • Partner with divisional product teams to define and mature strategic programs, including imaging algorithm development, data interoperability, and hospital solution implementation, ensuring each initiative has clear roadmaps, financial plans, governance, and resourced execution teams.
  • Support divisions in defining integration and implementation strategies for third-party data sources, such as EMR and EHR systems, aligning to enterprise standards for data governance, privacy, cybersecurity, and interoperability, including HL7 and FHIR where applicable.
  • Enable divisions to build AI and machine learning-enabled diagnostics and longitudinal care solutions by coordinating cross-functional requirements, risk assessments, and controls to support safe AI-enabled workflows across care settings.
  • Partner with divisions to accelerate physician workflow efficiency and improve clinical decision support by supporting adoption planning, training approaches, and changing management with clinical and hospital stakeholders.
  • Coordinate with AI Engineering, clinical experts, and divisional teams to set imaging AI initiatives up for success, including validation plans, dataset strategy, performance metrics, bias and risk considerations, and post-deployment monitoring expectations.
  • Support hospital-ready scalability by aligning deployment models, cybersecurity requirements, support models, and operational SLAs, while promoting reusable, enterprise-grade capabilities that reduce duplication and accelerate time to value.
  • Lead partnership selection and validation for Health AI vendors, including strategic fit, technical and Responsible AI due diligence, and clinical value assessment.
  • Coordinate vendor onboarding to meet enterprise needs across divisions, establish long-term collaboration models, integration standards, and governance expectations.
  • Manage vendor deliverables, contractual milestones, and performance in partnership with divisions, Procurement, Legal, Privacy, and Security teams.
  • Champion agile and compliant Health AI delivery practices in collaboration with divisions and data and AI delivery teams, leveraging AI-enabled tools for backlog management, sprint planning, and progress reporting.
  • Collaborate with Responsible AI, Regulatory, and Quality teams to standardize documentation, decision gates, and risk management artifacts, including alignment with software lifecycle controls and SaMD expectations where applicable.
  • Collaborate with divisions and delivery teams to define and report KPIs for adoption, outcomes, operational impact, and financial value realization, supporting corrective actions when needed.
  • Provide regular updates to leadership and governance councils, clearly communicating progress, risks, decisions required, and recommended trade-offs.

Qualifications:

Required Qualifications:

  • Bachelor's degree in business, engineering, computer science, biomedical engineering, or a related field.
  • Minimum of 7 years of experience in program management, product management, or digital delivery within a large, matrixed organization.
  • Demonstrated experience delivering AI and machine learning-enabled products or platforms, including vendor-led solutions, from discovery through launch and scale.
  • Hands-on experience leading cross-functional delivery across Clinical, IT or Enterprise Architecture, Security and Privacy, Regulatory and Quality, and external partners.
  • Working knowledge of digital and AI solutions, including clinical decision support, healthcare data interoperability, imaging AI, and diagnostic and predictive algorithms.
  • Strong vendor management and partnership evaluation skills, including technical due diligence, value hypothesis definition, and validation planning.
  • Strong analytical, problem-solving, and communication skills, with the ability to influence without direct authority and navigate ambiguity.

Preferred Qualifications:

  • Experience with imaging AI and computer vision products and associated clinical validation methods.
  • Experience with AI and machine learning algorithms used in clinical decision support and physician workflow management.
  • Experience with AI and machine learning enabled patient diagnostics and longitudinal care, including patient identification and stratification.
  • Experience with Responsible AI practices, model risk management, and post-market monitoring for AI solutions.
  • Familiarity with U.S. and EU regulatory considerations for AI-enabled medical software, including SaMD and emerging AI regulations.
  • Certification in Agile and or Product Management, such as CSPO, PSPO, SAFe, PMP, or equivalent.
  • Experience scaling enterprise vendor partnerships and onboarding solutions for multi-division reuse.