Senior Artificial Intelligence Engineer
Augusta University
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Benefits offered by this job
Job summary
Augusta University in Augusta, GA, seeks a Senior AI Engineer to lead the design, development, deployment, and operation of AI systems across healthcare research, clinical innovation, education, and enterprise initiatives.
The role combines software engineering, ML, data engineering, and AI infrastructure; you will mentor staff, set engineering standards, ensure secure, scalable solutions, and collaborate with researchers, clinicians, and IT teams. On-site requirement.
Qualifications
- Master's degree or PhD in a related field with 5+ years of professional AI/software experience.
- Experience in healthcare, clinical research, or regulated data environments is preferred.
- Strong Python and AI framework knowledge required.
- Experience mentoring engineers and leading complex AI projects.
Responsibilities
- Lead design and deployment of AI/ML/generative AI solutions for research and clinical initiatives.
- Design production-ready architectures including model serving, data pipelines, and orchestration.
- Develop MLOps pipelines and support on-premises, HPC, cloud, and hybrid environments.
- Guide API services, data workflows, and integration with institutional systems.
- Provide technical leadership, code standards, and mentoring.
- Identify opportunities for AI-enabled innovation and strategic growth.
Skills
Education
Tools
Job description
Job ID: 304559
Location: Augusta University
Full/Part Time: Full Time
Augusta University is Georgia's innovation center for education and health care, training the next generation of innovators, leaders, and healthcare providers in classrooms and clinics on four campuses in Augusta and locations across the state. More than 12,000 students choose Augusta for educational opportunities at the center of Georgia's cybersecurity hub and experiential learning that blends arts and application, humanities, and the health sciences. Augusta is home to Georgia's only public academic health center, where groundbreaking research is creating a healthier, more prosperous Georgia, and world‑class clinicians are bringing the medicine of tomorrow to patient care today. Our mission and values https://www.augusta.edu/about/mission.php make Augusta University an institution like no other.
Augusta University's distinct characteristics in education and research include real‑world experiences and community engagement, as well as a culture of building community, corporate and government partnerships that address health, security, economic and societal concerns locally and across the state.
More details on the USG Statement of Core Values and Code of Conduct are available in USG Board Policy 8.2.18.1.2 and can be found online at https://www.usg.edu/policymanual/section8/C224/#p8.2.18_personnel_conduct. Additionally, USG supports Freedom of Expression as stated in Board Policy 6.5 Freedom of Expression and Academic Freedom found online at https://www.usg.edu/policymanual/section6/C2653.
Our Health Sciences Campus: 1120 15th Street, Augusta, GA 30912
Our Summerville Campus: 2500 Walton Way, Augusta, GA 30904
The Department of AI and Health at Augusta University seeks an experienced Senior AI Engineer to lead the design, development, deployment, and operationalization of artificial intelligence systems supporting healthcare research, clinical innovation, education, and enterprise initiatives.
The Senior AI Engineer serves as a senior technical contributor and provides technical leadership across AI engineering projects. This position combines expertise in software engineering, machine learning, generative AI, data engineering, and AI infrastructure with the ability to translate research, clinical, and operational requirements into secure, scalable, reliable, and maintainable AI solutions.
Working collaboratively with AI engineers, data scientists, faculty, researchers, clinicians, analysts, and institutional technology teams, the Senior AI Engineer will lead solution architecture, establish engineering standards, support production AI platforms, mentor technical staff, and guide projects from prototype through production deployment.
This is not a telework position; on-site presence is required.
Lead the design, development, implementation, and deployment of AI, machine learning, and generative AI solutions supporting research, clinical, educational, and operational initiatives. Design production-ready AI architectures, including model serving, APIs, retrieval systems, data pipelines, vector databases, and workflow orchestration. Translate research, clinical, and operational requirements into scalable and maintainable technical solutions. Design systems with appropriate consideration for performance, availability, security, privacy, interoperability, and institutional requirements. Develop reusable architectures, services, and engineering patterns that support AI development across departmental projects.
Design, develop, and maintain pipelines supporting model development, validation, deployment, evaluation, monitoring, and lifecycle management. Implement automated testing, continuous integration and deployment, version control, and infrastructure provisioning practices. Support machine learning and generative AI workloads across on-premises, high-performance computing, cloud, and hybrid computing environments. Implement practices supporting reproducibility, observability, model and data versioning, governance, and auditability. Monitor and optimize AI systems for performance, scalability, reliability, and efficient use of computing resources.
Lead development of software components, APIs, services, applications, and data workflows supporting AI solutions. Establish and promote standards for code quality, testing, source control, documentation, code review, and deployment. Integrate AI capabilities with research systems, data platforms, clinical systems, and institutional technologies as appropriate. Collaborate with institutional technology, cybersecurity, data governance, and infrastructure teams to support secure and reliable AI deployments. Diagnose and resolve complex technical issues involving software, models, data pipelines, infrastructure, and deployment environments.
Design and implement applications using large language models and other foundation models. Develop retrieval-augmented generation, semantic search, knowledge retrieval, tool-enabled AI, and agentic AI workflows where appropriate. Implement methods for evaluating AI systems for accuracy, reliability, performance, safety, and appropriate use. Support deployment and optimization of open-source and commercial AI models across institutional computing environments. Evaluate emerging AI technologies and recommend appropriate technologies, platforms, and architectural approaches.
Serve as a senior technical resource and subject matter expert for AI engineering initiatives. Provide technical leadership during project planning, architecture design, implementation, code review, and deployment. Mentor AI engineers, analysts, students, and other technical staff in modern AI engineering practices. Establish and promote engineering standards, reusable technical patterns, and documentation practices. Collaborate with faculty, researchers, clinicians, analysts, and institutional partners to define requirements and develop effective technical solutions. Coordinate technical activities across multiple projects and identify technical dependencies, risks, and resource requirements.
Identify opportunities to apply artificial intelligence and automation to advance research, clinical innovation, education, and institutional operations. Collaborate with investigators on the technical design and implementation of AI-enabled research projects. Provide technical expertise for grant proposals, including architecture, technical feasibility, infrastructure requirements, and implementation planning. Develop prototypes and proof‑of‑concept systems to evaluate emerging AI approaches. Contribute to departmental planning for AI infrastructure, platforms, engineering capabilities, and technical strategy. Support technical publications, presentations, demonstrations, and knowledge‑sharing activities.
Maintain expertise in artificial intelligence, machine learning engineering, software engineering, data technologies, cybersecurity, and computing infrastructure. Remain current with emerging developments in generative AI, foundation models, AI engineering frameworks, and responsible AI practices. Participate in relevant training, professional development, and technical communities.
Perform other duties and special projects as assigned.
- Master's degree from an accredited college or university and five years of professional experience in software engineering, machine learning, artificial intelligence, data engineering, cloud computing, or related field.
- or Bachelor's degree from an accredited college or university and seven years of professional experience in software engineering, machine learning, artificial intelligence, data engineering, cloud computing, or related field.
PhD from an accredited college or university in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Engineering, or a related field. OR Master's degree from an accredited college or university in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Data Engineering, Software Engineering, Computer Engineering, or a closely related field.
Experience developing, deploying, or operating large language models and generative AI applications. Experience with retrieval-augmented generation, semantic search, vector databases, or agentic AI systems. Experience deploying machine learning or AI workloads on GPU-based computing infrastructure. Experience with cloud platforms such as Azure, AWS, or Google Cloud Platform. Experience with containerization and orchestration technologies such as Docker and Kubernetes. Experience developing APIs, microservices, distributed applications, or data-intensive systems. Experience implementing MLOps, DevOps, automated testing, and CI/CD practices. Experience with high-performance computing, on-premises AI infrastructure, or hybrid computing environments. Experience in healthcare, biomedical research, clinical research, academic research, or another regulated data environment. Familiarity with healthcare privacy, security, research compliance, and data governance requirements. Experience supporting interdisciplinary or grant-funded research initiatives. Experience mentoring engineers or providing technical leadership across complex projects.
Advanced knowledge of software engineering principles, system architecture, and AI application development. Strong proficiency in Python and relevant AI and machine learning frameworks and libraries. Strong understanding of machine learning and generative AI application architectures. Knowledge of large language models, retrieval-augmented generation, embedding technologies, vector databases, and AI application orchestration. Knowledge of APIs, distributed systems, containerization, and modern application architecture. Strong understanding of DevOps, MLOps, automated testing, deployment, monitoring, and software lifecycle practices.
Strong analytical, troubleshooting, and problem‑solving skills. Strong written and verbal communication skills, including the ability to communicate technical concepts to technical and nontechnical audiences.
Ability to design scalable, maintainable, secure, and reliable technical solutions. Ability to evaluate technical alternatives and make architecture and implementation recommendations. Demonstrated ability to lead technical initiatives, work effectively across multidisciplinary teams, and mentor less experienced technical staff. Ability to manage technical responsibilities across multiple projects and priorities.
Days; M-F (Work outside of the standard business hours may be required)
B17
$109,500/annually-$139,600/annually Salary to be commensurate with qualifications of the selected candidate within the established range (generally minimum-midpoint) of the position
10/7/26 - Until Filled
- Health insurance
- Dental insurance
- Life insurance
- Teachers Retirement System (or Optional Retirement Plan)
- Earned vacation time
- Sick leave
- 13 paid holidays
- Tuition Assistance Program
All selected candidates are required to successfully pass a Background Check review prior to starting with Augusta University. If applicable for the specific position based on the duties: the candidate will also need to have a credit check completed for Positions of Trust and or approved departmental Purchase Card usage. Motor vehicle reports are required for positions that are required to drive an Augusta University vehicle. For Faculty Hires: Final candidates will be required to provide proof of completed academic degree(s) as well as post‑secondary coursework in the form of original transcript(s). Those candidates trained by a foreign institution will also be required to provide an educational/credential evaluation. All employees are responsible for ensuring the confidentiality, availability, and integrity of sensitive [patient, student, employee, financial, business, etc.] information by exercising sound judgment and adhering to cybersecurity and privacy policies during their employment and beyond.
Augusta University is proud to be an equal opportunity employer welcoming applicants from underrepresented groups, including individuals with disabilities and veterans.
This position is also responsible for promoting a customer‑friendly environment and providing superior service to our patients, students, faculty, and employees. "Augusta University is a patient‑and family‑centered care institution, where employees partner every day with patients and families for success." Augusta University is a tobacco‑free environment, and the use of any tobacco products on any part of the campus, both inside and outside, is strictly prohibited.
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