AIML Solutions Architect

Company Overview:

Over the past 15 years eTel has delivered essential solutions for the federal government by securing and managing data providing scalable identity access modernizing legacy systems and building high-performance platforms. By integrating new technologies and ensuring reliable operations we help agencies stay prepared for future challenges As a premier technology solutions and services company to the US federal government eTel possesses longstanding relationships across the federal civilian marketplace. Other customers include the broader Treasury Department Commerce Department and State Department.

eTel offers integrated CMMI Level 3 processes tools and techniques with innovative cost-efficient and secure solutions to address complex challenges. eTel also holds ISO 9001:2015 ISO/IEC 27001:2013 and ISO/IEC 20000-1:2018 certifications and offers dedicated subject matter experts (SMEs) and thought leaders that possess a deep understanding of customers environments and challenges.

Work Location and On-Site/Telework Requirements: Hybrid NIH Bethesda MD. On site for discovery workshops (typically 12 days/week during the first 120 days then as scheduled).

Citizenship: U.S. Citizenship required

Clearance: All staff must obtain NIH suitability and a PIV credential and be fluent in English. Anyone doing risk or vulnerability testing needs a current T2 (BI) or higher investigation.

Overview:

You will lead Task 3 AI-Enabled Zero Trust Use Case Identification and Development under the NIH Governance Risk & Compliance (GRC) Zero Trust Architecture (ZTA) Support Services task order for the NIH Office of the Chief Information Officer (OCIO). Working in the Architecture Pod you will find where AI can improve Zero Trust policy decisions design how those signals feed enforcement and measure whether they are worth deploying. All of this work must fit NIHs AI governance and data-governance requirements.

Responsibilities:

• Lead a six-week discovery with ISAO GRC OITA and CIT to build the AI Use Case Inventory across all ZTA pillars (Subtask 3.1 due at 120 days).
• Score each use case on risk reduction feasibility with NIHs current telemetry mission impact and data-governance readiness then tier it as deploy now design next or watch.
• Record for each use case its NIST AI RMF 1.0 function (Govern Map Measure Manage) data classification human-in-the-loop requirement and OMB AI use-case inventory disposition.
• Produce the AI technical architectures (Subtask 3.2): data-flow diagrams; model requirements (inputs features retraining cadence drift thresholds); trust-scoring logic written as policy-as-code that the Policy Engine can consume; and integration patterns for identity-provider risk APIs endpoint compliance evaluation network policy controllers and SOAR playbooks.
• Design use cases such as continuous authentication risk scoring credential-misuse detection device risk classification from EDR/MDM telemetry API and workload-identity anomaly detection ML classification of PHI/PII/research data UEBA for insider risk and AI-assisted SOAR triage.
• Extend Zero Trust to AI agents and copilots: authorization of individual agent actions and tool calls data-leakage controls and prompt-injection risk.
• Define and run the Subtask 3.3 measurement protocol (detection rate false-positive rate time to detect analyst hours saved enforcement latency) in controlled evaluations on NIH telemetry. Recommend whether each capability should enforce or stay advisory.

Tools & Technology Environment: Python scikit-learn PyTorch; UEBA and analytics in Splunk/Microsoft Sentinel; identity risk signals (e.g. Microsoft Entra ID Protection); EDR/MDM telemetry (Defender CrowdStrike); SOAR platforms; Azure AI/AWS SageMaker or Bedrock; policy-as-code (e.g. OPA/Rego).

Required Qualifications:

• Bachelors degree in computer science data science or a related field plus 8 years of experience including AI/ML use-case design.
• Experience designing risk or trust-scoring models on security telemetry (identity endpoint network or SIEM data).
• Working knowledge of the NIST AI RMF 1.0 and federal AI governance expectations.
• Hands-on Python and ML framework experience.
• Ability to obtain an NIH suitability determination and PIV credential; fluent in English.

Preferred Qualifications:

• Masters degree; experience with the NIST AI RMF Generative AI Profile and current OMB AI memoranda.
• Familiarity with NIST SP 800-207 MITRE ATLAS and the OWASP Top 10 for LLM Applications.
• Experience with PHI/PII or health research data governance.
• Security certification (Security CISSP) or cloud AI certification.
• Current National Institutes of Health (NIH) or U.S. Department of Health and Human Services (HHS) experience is highly preferred.

Commitment to Diversity -
eTelligent Group provides equal employment opportunities (EEO) to all applicants without regard to race color religion gender sexual orientation gender identity nations origin age disability genetic information marital status amnesty status as a covered veteran and any other characteristic provided in accordance with applicable federal state and local laws.