Telework Eligible

Yes

Major Duties

• Translates responsible artificial intelligence expectations into specific technical requirements and implementation approaches that can be applied to AI-enabled systems operating in development, test, and production environments.
• Recommends or develops engineering patterns for safe integration of AI into operational environments, including guardrails for user interaction, logging, monitoring, workflow constraints, and controls on model-driven outputs.
• Assesses AI-enabled systems such as to determine whether the technical safeguards, evaluation evidence, and operational conditions are adequate for use.
• Communicates technical findings to leadership, governance stakeholders, and engineering teams in a form that supports approval decisions, remediation plans, sustainment reviews, and continued oversight of deployed AI capabilities.
• Works with developers, AI engineers, machine learning engineers, software engineers, cybersecurity personnel, and program stakeholders to ensure that needed evidence is created and retained as part of the system lifecycle.
• Serves as the senior technical advisor on responsible AI assurance, control implementation, evaluation methods, and AI-related risk treatment across DLA AIACoE efforts and supported organizations.
• Develops, updates, and maintains standards, playbooks, implementation guides, technical references, and training materials supporting responsible AI engineering, assurance, evaluation, documentation, and governance implementation across DLA.

Qualification Summary

To qualify for a Responsible AI Engineer, 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: Reviews system designs, workflows, service interactions, data dependencies, and integrated application behavior to identify where assurance controls are needed and how those controls should be implemented. Evaluates whether AI systems include sufficient controls to support accountability, reproducibility, and operational oversight. Establishes consistent evidence requirements for AI systems to support governance reviews, management decisions, audit readiness, sustainment reviews, and corrective action follow-through. Advises on technical tradeoffs involving control implementation, usability, monitoring, sustainment burden, deployment timing, operational constraints, model limitations, and governance readiness. 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.

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