AI Technical Product Architect

What We Offer

⭐This is a Remote Position⭐ Candidates can be located in any state EXCEPT NY, NJ, CA, and IL.

🚀 The Technical Product Architect - Artificial Intelligence (AI) owns “the How, Execution of the How, and By When” for the product team’s Artificial Intelligence solutions. This role primarily serves as the Solutions Architect for the product team, but is also able to function as Principal Engineer. The Technical Product Architect - Artificial Intelligence (AI) specializes in designing and delivering solutions in one or more primary domains: patient experience, clinical care, and/or health system operations.

Leveraging key “product operating model” principals from the Silicon Valley Product Group (SVPG), the Technical Product Architect - Artificial Intelligence (AI) focuses primarily on architecture and principal engineering by ensuring technical feasibility, business alignment, and adherence to AI best practices through collaboration with technical teams, product managers, and stakeholders. As a driving force behind AI transformation, this leader will shape cutting‑edge solutions that revolutionize healthcare, turning innovation into real‑world impact that improves lives and redefines what’s possible.

• 4 years of experience leading or mentoring a team of software engineers.
• Minimum of 2 years of experience in machine learning (ML/AI) engineering.

• Agile & Dev Ops Experience – Strong understanding of Agile methodologies, CI/CD pipelines, and Dev Ops practices to drive efficient AI/ML model deployment and lifecycle management.
• Experience with Artificial Intelligence and Machine Learning Frameworks – A broad understanding of AI/ML algorithms, common architectures, AI/ML application development, and MLOps to inform effective guidance of technical teams spanning predictive models, generative AI, retrieval‑augmented generation (RAG), and Agentic AI.
• Responsible AI mindset – A strong commitment to developing AI solutions ethically, including understanding potential biases, ensuring transparency, and complying with all relevant regulations.
• Outcomes‑oriented Thinking and Business Acumen – Capacity to align AI initiatives with organizational goals, identify innovative solutions, and drive value through technology by understanding healthcare‑specific challenges. Demonstrated track record of bridging technical depth with product thinking, collaborating with product managers, designers, engineers, and stakeholders to ensure technical investments accelerate product outcomes. Approach new opportunities with curiosity.
• Excellent Communication Skills – Ability to articulate complex technical concepts to non‑technical stakeholders, collaborate with various departments and stakeholders, and translate needs into technical requirements.
• Systems Design & Scalability Expertise – Ability to design AI solutions that integrate seamlessly into complex healthcare ecosystems while considering scalability, interoperability, and system performance leveraging novel and industry‑standard patterns and principles.
• Cloud & Data Infrastructure Knowledge – Proficiency in cloud platforms (AWS, Azure, GCP) and data engineering principles, including data pipelines, security, governance, and compliance in healthcare AI solutions.
• A positive “get to yes” attitude – Seek to find a solution that meets viability, value, feasibility, and usability objectives.

• Education:
  
  4‑Year / Bachelor’s Degree required in Engineering, Computer Science or a similar field.
• Experience
  • Required – 2 years of experience in a technical product architecture role in software engineering, machine learning/AI engineering, data engineering, or similar.
  • Required – 4 years of experience in a lead and/or senior engineering role within a technology organization with a focus on leading software engineers to develop software products.
• Additional Skills (required)
  • Extensive Technical Expertise – Act as a technology consultant and partner, providing solution architecture designs across multiple technical domains and analyzing options in terms of technical feasibility, implementation effort, and performance targets. Understand…