Overview:
Must be a US Citizen or Permanent Resident
Remote position
W2 with full benefits
Ongoing Contract supporting ARPA-H
The US base salary range for this position is $121-210K + benefits. Salary ranges are determined by role, level, and location. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position across all US locations. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training.
Responsibilities:
Key Role: This Systems, Engineering and Technical Assistance (SETA) role will provide technical support to an the Program Manager and a new program. As a Senior AI Engineer and Applications Scientist, you will apply your expertise to help conceptualize, create, and execute government funded research and development programs to meet the organization’s mission to accelerate better health outcomes for everyone.

This SETA duties included but are not limited to:

• Contribute to a multidisciplinary team developing breakthrough Generative AI and agentic applications for the diagnosis and management of acute and chronic disease.
• Provide subject matter expertise in clinical application of AI, the current and next generations of Generative AI and Agentic AI applications.
• Evaluate technical proposals for scientific merit and innovation. Provide feedback, organize reviewer comments, draft recommendations and project summaries, and presentation materials.
• Perform market and regulatory analyses, technical due diligence, literature reviews and generate briefing documents summarizing technical topics related to AI, medical grade LLMs, Electronic Health Record (EHR) integration with AI, and U.S. Food and Drug Administration (FDA) and Center for Medicare and Medicaid Services (CMS) regulation of AI Agents.
• Develop technical and administrative programmatic documentation on short timelines to communicate technical approach, progress, cost, schedule and risk for development of diagnostic grade AI agents.

Qualifications:

Required Skills:

• A PhD is preferred, MS with 2+ years or a BA with 4+ years is acceptable. Given the field of expertise, years of experience and professional certifications are likely valued over academic degrees. Further, an educational degree may not be required if the candidate’s experience is sufficient to meet the requirements outlined above.
• Team oriented with exceptional communication, writing, and organizational skills.
• Experience in health care application development involving access to electronic health records (EHR) and/or use of EHR data.
• Experience in the development and/or evaluation of generative AI applications e.g., LLMs, AI agents.
• Familiarity with industry leaders and disrupters in advanced AI development (e.g. the AI development landscape).
• Remote is acceptable.

Additional Experience:

• Prior experience supporting ARPA-like programs (e.g., DARPA, IARPA, APRA-E) or U.S. DoD advanced development programs is desired, but not required.

• Contribute to a multidisciplinary team developing breakthrough Generative AI and agentic applications for the diagnosis and management of acute and chronic disease.
• Provide subject matter expertise in clinical application of AI, the current and next generations of Generative AI and Agentic AI applications.
• Evaluate technical proposals for scientific merit and innovation. Provide feedback, organize reviewer comments, draft recommendations and project summaries, and presentation materials.
• Perform market and regulatory analyses, technical due diligence, literature reviews and generate briefing documents summarizing technical topics related to AI, medical grade LLMs, Electronic Health Record (EHR) integration with AI, and U.S. Food and Drug Administration (FDA) and Center for Medicare and Medicaid Services (CMS) regulation of AI Agents.
• Develop technical and administrative programmatic documentation on short timelines to communicate technical approach, progress, cost, schedule and risk for development of diagnostic grade AI agents