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A leading healthcare technology firm is seeking an AI Architect to design scalable and innovative AI systems. This role involves developing multi-agent solutions, evaluating frameworks, and mentoring engineers. Applicants should have strong Python skills, experience with cloud platforms, and a robust understanding of AI and data governance. Competitive benefits are offered, promoting employee wellness and flexibility.
RLDatix (RLD) is on a mission to help raise the standard of care…everywhere. Trusted by over 10,000 healthcare organizations around the world, our solutions help improve health and care. Our applications ensure that patients receive the best and safest care while supporting the providers who deliver it.
Joining TeamRLD means being part of a global effort of over 2,000 team members in making a difference in healthcare…every day.
We’re searching for an AI Architect to join our Engineering team, so that we can design and deliver next-generation AI systems that power safer, more efficient healthcare solutions. The AI Architect will lead the design and implementation of agentic AI architectures, ensuring scalability, innovation, and measurable client impact.
By enabling flexibility in how we work and prioritizing employee wellness, we empower our team to do and be their best. Our benefits package includes health, dental, vision, life, disability insurance, 401K, paid time off, and paid holidays.
RLDatix is an equal opportunity employer, and our employment decisions are made without regard to race, color, religion, age, gender, national origin, disability, handicap, marital status or any other status or condition protected by Federal and/or State laws.
As part of RLDatix’s commitment to the inclusion of all qualified individuals, we ensure that persons with disabilities are provided reasonable accommodation in the job application and interview process. If reasonable accommodation is needed to participate in either step, please don’t hesitate to send a note to accessibility@rldatix.com.
Salary offers are based on a wide range of factors including location, relevant skills, training, experience, education, and, where applicable, licensure or certifications obtained. Market and organizational factors are also taken into consideration.