SME AI Governance Specialist

Leidos

AI Governance Specialist developing and maintaining frameworks for AI compliance with ethical and legal standards. Collaborating across teams to ensure AI solutions meet governance policies and requirements.

Posted 5/27/2026full-timeAlexandria • Maryland, Virginia • 🇺🇸 United StatesSeniorLead💰 $131,300 - $237,350 per yearWebsite

Tech Stack

Tools & technologies

AWSAzureCloudCyber SecurityDockerGoogle Cloud PlatformKubernetesTypeScriptVMware

About the role

Key responsibilities & impact

Develop and maintain AI governance frameworks ensuring compliance with ethical, legal, and organizational standards
Conduct risk assessments to identify potential harms, biases, or compliance gaps in AI models and workflows
Collaborate with engineering, legal, and mission teams to ensure AI solutions align with governance policies
Prepare, maintain, and execute a System Engineering Plan (SEP) for managing all systems architecture and system engineering aspects
Design, prepare, and document systems engineering and cybersecurity artifacts for the System
Conduct systems engineering activities to specify, build, and maintain system engineering designs
Support the Government in recommending and conducting enterprise system architecture activities
Define, document, maintain, and promulgate APIs and technical standards for the System
Design, engineer, integrate, and continuously improve the underlying infrastructure of the System
Identify, prepare, track, secure, and integrate government, commercial, and open-source tools and services into the System
Design, architect, engineer, and continuously improve the user interface (UI) and user experience (UX) components
Build and maintain services and products to make production-ready AI/ML models accessible for customer use
Design, architect, engineer, and continuously improve all aspects of cybersecurity elements of the System
Perform site reliability engineering to build and maintain a reliable, scalable, and efficient System
Participate in the Engineering Control Board (ECB) process for supporting all major engineering milestones and decisions

Requirements

What you’ll need

Active Top Secret (TS) clearance with SCI eligibility
Bachelor’s degree in Computer Science, Data Science, Artificial Intelligence, Engineering, Information Systems, or related technical discipline and 12–15 years of relevant experience OR Master’s degree in a related field and 10–13 years of relevant experience
Minimum of 8 years of experience in systems engineering, AI governance, data governance, or a related field
Strong understanding of ethical, legal, and organizational standards for AI systems
Experience implementing AI/ML governance or responsible AI frameworks in enterprise environments
Experience evaluating AI/ML models for performance, bias, explainability, and risk
Experience integrating governance controls into AI/ML DevSecOps pipelines
Experience supporting AI systems in cloud-native environments (AWS, Azure, or GCP)
Proficiency in systems engineering and cybersecurity practices
Experience with enterprise system architecture activities
Ability to define and maintain APIs and technical standards
Experience with cloud environments, data storage, and DevSecOps practices
Demonstrated expertise in AI lifecycle management and policy-to-implementation alignment
Experience developing Agentic AI solutions, including autonomous planning–execution–reflection loops, multi-agent collaboration and coordination, and tool usage patterns including API integration, retrieval-augmented generation (RAG), and memory/context management
Solid understanding and hands-on experience with generative AI models including prompt engineering, chain-of-thought reasoning, and Natural Language Processing (NLP) tasks such as entity extraction, summarization, and semantic search
Working knowledge of Large Language Models (LLMs) and agent frameworks such as LangChain, LangGraph, CrewAI, A2A, MCP, or AutoGen
Experience using vector databases (e.g., Pinecone, Weaviate, FAISS)
Familiarity with deployment into virtualized and containerized environments (e.g., VMware, Docker, Kubernetes)

Benefits

Comp & perks

competitive compensation
Health and Wellness programs
Income Protection
Paid Leave
Retirement

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

AI governancesystems engineeringcybersecurityAI/ML governanceDevSecOpsNatural Language Processing (NLP)generative AI modelsAPI integrationrisk assessmentperformance evaluation

Soft Skills

collaborationcommunicationproblem-solvingorganizational skillsleadership

Certifications

Top Secret (TS) clearance with SCI eligibility