Supervisory IT Project Manager (SYSANALYSIS/PLCYPLN)
Telework Eligible
Yes
Major Duties
Qualification Summary
To qualify for a Supervisory IT Project Manager (SYSANALYSIS/PLCYPLN), your resume and supporting documentation must support: A. Specialized Experience: One year of specialized experience that equipped you with the particular competencies to successfully perform the duties of the position and is directly in or related to this position. To qualify at the GS-14 level, applicants must possess one year of specialized experience equivalent to the GS-13 level or equivalent under other pay systems in the Federal service, military, or private sector. Applicants must meet eligibility requirements including time-in-grade (General Schedule (GS) positions only), time-after-competitive appointment, minimum qualifications, and any other regulatory requirements by the cut-off/closing date of the announcement. Creditable specialized experience includes: Assesses AI risks related to data, models, operational environment, ethical, societal, legal, and compliance. Evaluates risks based on impact to the organization and society. Categorizes risks based on severity and likelihood. Uses knowledge and understanding of the complex interrelationships of multiple IT specialties to ensure the integration of IT programs and services adhere to AI responsible use risk management and internal management control activities developing solutions to issues. Develops risk mitigation plan and implement safeguards such as explainable AI, bias detection tools, and robust testing processes. Develops an incident response plan to respond to AI risks such as algorithmic failure or misuse. Executes and coordinates the planning, organizing, controlling, and integrating of the AI risk management and internal management control programs and initiatives within the company ensuring compliance with requirements to manage risks from the use of AI. Experience working with interdisciplinary teams of data scientists, engineers, and risk and policy experts. Experience in identifying, assessing, and mitigating risks associated with AI/ML systems, including biases, security vulnerabilities, and ethical concerns. Experience in ensuring compliance with laws and regulations, such as DoD AI Ethical Principles, Privacy Act, and Federal Acquisition Regulations. Knowledge of AM/ML frameworks, algorithms, and tools, as well as their practical applications. Experience refers to paid and unpaid experience, including volunteer work done through National Service programs (e.g., Peace Corps, AmeriCorps) and other organizations (e.g., professional, philanthropic, religious, spiritual, community, student, social). Volunteer work helps build critical competencies, knowledge, and skills and can provide valuable training and experience that translates directly to paid employment. You will receive credit for all qualifying experience, including volunteer experience.
The Nation's Logistics Combat Support Agency, responsible for delivering agile, adaptive, and resilient logistics support across the continuum of conflict.