About this role

MANDATORY QUALIFICATION CRITERIA: For this particular job, applicants must meet all competencies reflected under the Mandatory Qualification Criteria to include education (if required). Online resumes must demonstrate qualification by providing specific examples and associated results, in response to the announcement's mandatory criteria specified in this vacancy announcement: 1. Demonstrated experience evaluating AI systems by executing standardized benchmarking protocols on AI platforms (e.g., Gemini Pro; GPT-4, Claude, or Llama-based frameworks).

2. Demonstrated experience scaling AI capabilities by transitioning enterprise-level automation platforms, from testing environments to live production. 3. Demonstrated experience auditing AI models by either formal vulnerability or bias assessments on AI services (e.g., Retrieval-Augmented Generation (RAG) systems; autonomous agents, or multimodal image/audio classifiers) prior to operational deployment. EDUCATION REQUIREMENT: A.

Education: Bachelor's degree from an accredited college or university in Data Analytics, Business Intelligence, Mathematics, Statistics, Actuarial Science, Computer Science, Engineering, Information Design, Operations Research, Finance, Information Technology, or a related field. -OR- B. Combination of Education and Experience: A minimum of 24 semester (36 quarter) hours of coursework in any area listed in option A, plus experience that requires the application of tools and algorithms to identify trends and patterns in data, or in a related area that demonstrates the ability to successfully perform the duties associated with this work.

As a rule, every 30 semester (45 quarter) hours of coursework is equivalent to one year of experience. Candidates should show that their combination of education and experience totals 4 years. DESIRABLE QUALIFICATION CRITERIA: In addition to the mandatory qualifications, experience in the following is desired: 1. Demonstrated experience evaluating technical architectures by assessing system dependencies, model documentation, or implementation plans in support of enterprise adoption decisions.

2. Demonstrated experience utilizing secure enterprise infrastructure by deploying or integrating AI models within large-scale, highly regulated environments (e.g., IC Foundational AI Stack, AWS GovCloud, or financial/commercial equivalents). 3. Demonstrated experience building AI capabilities by designing or scaling operational AI or automation platforms, resulting in measurable improvements to business workflows, mission effectiveness, or operational efficiency.

4. Demonstrated experience overseeing technical vendors through technical execution management, contractor oversight, or procurement processes for AI or software contracts (e.g., serving as a Contracting Officer's Representative (COR), Technical Monitor, or commercial Vendor Manager). 5. Demonstrated experience validating AI data pipelines by assuring the quality of input datasets for model training, fine-tuning, or performance testing initiatives.

Source listing: usajobs