AI/LLM Systems Engineer; Information Systems Specialist Hybrid s; perma
Listed on 2026-03-02
-
IT/Tech
AI Engineer, Data Analyst, Systems Engineer
Initial Posting Date: 02/26/2026
Final date to receive applications: 03/08/2026
Agency: Oregon Health Authority
Position Type: Employee
Position Title: AI/LLM Systems Engineer (Information Systems Specialist
6) Hybrid work options (Full-time permanent position)
6) Hybrid work options
As an AI/LLM Systems Engineer
, you will play a pivotal role in planning, developing, integrating, implementing, and coordinating projects and activities related to Artificial Intelligence and Large Language Models (LLMs). This specialist position focuses software development that integrates with AI/LLM models, business analysis, research, problem‑solving, and system administration.
The AI/LLM Systems Engineer will design, develop, and maintain software systems that integrate AI/LLM components, collaborating with staff and management to turn business needs into practical solutions. You will participate in system development lifecycle planning, contribute to technical recommendations, and support both new development and ongoing system modifications and updates.
The AI/LLM Systems Engineer is assigned work in terms of program and project objectives, priorities, and timelines. This position consults with supervisors and team leads to resolve policy questions and problems in coordinating activities with other programs. Typically, work is subject to technical and administrative control in which review is made of program or project accomplishments and adherence to policies, directives, and desired results.
For a full review of the position description, please .
What We Are Looking ForMinimum Qualifications: These qualifications must be reflected in your application for consideration.
(a) Five (5) years of information systems experience in Software Development/Data Management or related field.
OR
(b) An Associate's degree in Computer Science, Information Technology, or related field,
OR
completion of a two (2) year accredited vocational training program in information technology or related field.
AND
three (3) years of information systems experience in Software Development/Data Management or related field.
OR
(c) A Bachelor's degree in Information Technology, Computer Science, or related field
AND one (1) year of information systems experience in Software Development/Data Management or related field.
OR
(d) Master's degree in Information Technology, Computer Science, or related field.
Desired Attributes- Ability to work with some guidance when performing development functions, establishing personal work priorities, resolving issues in alignment with business priorities, technical standards, organization practices, enterprise frameworks and paradigms.
- Experience with one or more of the following common Software Development technologies such as:
Microsoft Azure, .NET, Python, Azure Dev Ops, Microsoft OS and SQL Server, and an expectation to gain skills in the remaining skillsets. - Develop and implement solutions using Large Language Models to enhance search functionality within our internal documentation systems.
- Develop and build scalable and efficient search systems that leverage LLMs for better retrieval and contextual understanding of documentation.
- Ability to integrate systems and applications using RESTful APIs, Azure API Management, and other Azure services.
- Strong knowledge of Azure Integration services such as Logic Apps, API Management, Service Bus, and Event Grid for building scalable and secure integration solutions.
- Some experience using modern Dev Ops tools including source control systems, testing practices, code and design review tools and processes such as ADOS, Git, Sonar Qube and Burp
- Experience in advancing health equity, addressing systemic health disparities, and collaborating with diverse, vulnerable, and underrepresented populations.
Preference may be given to candidates who are bilingual or multilingual and can assist with AI model translation, language validation, and cross-linguistic quality review.
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