SME AI Governance Specialist

🕒 May 27

🇺🇸 United States – Remote

💵 $131.3k - $237.3k / year

⏰ Full Time

🟠 Senior

🔴 Lead

🤖 Artificial Intelligence

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Leidos

WebsiteLinkedInAll Job Openings

10,000+ employees

Founded 1969

🔒 Cybersecurity

🔬 Science

Defense • Cybersecurity • Science

Leidos is a leading systems integrator in science, technology, and engineering, providing solutions that transform and enable the missions of its customers. The company operates across various markets, including aviation, defense, energy, government, healthcare, intelligence, science, and space. Leidos is involved in AI, digital modernization, cyber operations, and integrated and mission software systems. With a commitment to diversity, equity, inclusion, and sustainability, Leidos also engages in charitable efforts and community enrichment programs. Additionally, it contributes to developing solutions for counter-unmanned aerial systems and electric vehicle infrastructure for military applications.

📋 Description

• 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

• Active Secret clearance with TS/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

• Health and Wellness programs • Income Protection • Paid Leave • Retirement