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Manager Artificial Intelligence Jobs in Virginia

PenFed Credit Union

SVP Artificial Intelligence

Mclean, VA

$158K - $198K/yr

Overview PenFed is hiring a SVP Artificial Intelligence at our Tysons, Virginia location. The ... AI Management--establishing and overseeing the enterprise framework for AI lifecycle management ...

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Manager Artificial Intelligence information

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$28.2K

$132.1K

$194K

How much do manager artificial intelligence jobs pay per year?

As of Aug 17, 2026, the average yearly pay for manager artificial intelligence in Virginia is $132,098.00, according to ZipRecruiter salary data. Most workers in this role earn between $94,821.00 and $171,165.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a manager of artificial intelligence?

To thrive as a Manager of Artificial Intelligence, you need a strong background in computer science, machine learning, and data analytics, often supported by advanced degrees and experience in AI project leadership. Familiarity with AI frameworks such as TensorFlow or PyTorch, experience with cloud platforms, and certifications like AWS Certified Machine Learning are typically valued. Strong leadership, strategic thinking, and effective communication are vital soft skills for guiding teams and aligning projects with business goals. These skills ensure successful development and deployment of AI solutions that drive organizational value and innovation.

How does a manager of artificial intelligence typically collaborate with cross-functional teams within an organization?

A Manager of Artificial Intelligence frequently works alongside data scientists, engineers, product managers, and business stakeholders to align AI initiatives with organizational goals. They facilitate communication between technical and non-technical teams, ensuring that project requirements are clearly understood and that AI solutions support broader business strategies. This collaborative environment often involves regular meetings, progress updates, and joint problem-solving sessions to address challenges and optimize outcomes.

How do you become a Manager Artificial Intelligence?

To become a Manager of Artificial Intelligence, candidates typically need a strong background in computer science, data science, or related fields, along with experience in AI development, machine learning, and leadership. Earning advanced degrees such as a master's or Ph.D. and gaining experience with AI tools and frameworks like TensorFlow or PyTorch are common steps. Leadership skills and knowledge of project management are also important for overseeing AI teams and projects.

What does a manager of artificial intelligence do?

A Manager of Artificial Intelligence oversees teams and projects that develop and implement AI solutions within an organization. Their responsibilities include setting strategic goals for AI initiatives, managing budgets and timelines, coordinating with other departments, and ensuring that AI systems are aligned with business objectives. They also stay updated on the latest advancements in AI technologies and ensure ethical standards and compliance are maintained. This role requires both technical knowledge of AI and strong leadership skills to guide multidisciplinary teams.

What is the difference between Manager Artificial Intelligence vs Data Scientist?

AspectManager Artificial IntelligenceData Scientist
CredentialsMaster's or PhD in AI, Computer Science, or related fieldsMaster's or PhD in Data Science, Statistics, or related fields
Work EnvironmentLeads AI projects, manages teams, collaborates with stakeholdersAnalyzes data, develops models, interprets results
Industry UsageUsed in organizations deploying AI solutions, tech companies, R&DUsed across industries for data analysis, predictive modeling

The main difference is that a Manager Artificial Intelligence oversees AI projects and teams, focusing on strategy and implementation, while a Data Scientist primarily analyzes data and builds models. Managers handle leadership and project management, whereas Data Scientists focus on technical analysis and model development.

What are the most commonly searched types of Artificial Intelligence jobs in Virginia?

The most popular types of Artificial Intelligence jobs in Virginia are:

What are popular job titles related to Manager Artificial Intelligence jobs in Virginia?

For Manager Artificial Intelligence jobs in Virginia, the most frequently searched job titles are:

What job categories do people searching Manager Artificial Intelligence jobs in Virginia look for?

The top searched job categories for Manager Artificial Intelligence jobs in Virginia are:

What cities in Virginia are hiring for Manager Artificial Intelligence jobs?

Cities in Virginia with the most Manager Artificial Intelligence job openings:

Manager Artificial Intelligence jobs near you

Artificial Intelligence Cybersecurity Engineer

Entarian

Arlington, VA • On-site

Full-time

Re-posted 16 days ago

Job description

Overview/ Job Responsibilities
We are seeking a skilled Artificial Intelligence Cybersecurity Engineer to join our team and ensure the seamless deployment, monitoring, and optimization of AI models in production.
Sev1Tech is seeking an AI Integration Engineer to integrate AI models into production systems, ensuring robust performance, real-time monitoring, and secure operations. The AI Integration Engineer will bridge the gap between AI model development and production systems, integrating models into applications, APIs, and infrastructure. This role focuses on building dashboards for real-time and historical model health, detecting data drift, and managing AI logging, while ensuring secure-by-design practices and alignment with business objectives.
Key Responsibilities
  • Model Integration: Integrate AI/ML models into applications (e.g., web, mobile, IoT) using APIs (REST, gRPC) and platforms like TensorFlow Serving or AWS SageMaker.
  • Dashboard Development: Create real-time and historical dashboards using Grafana, Kibana, or Plotly to monitor model health (e.g., latency, accuracy) and data drift.
  • Drift and Health Monitoring: Implement monitoring pipelines with tools like Evidently AI or Weights & Biases to detect data drift and model degradation, triggering alerts as needed.
  • Logging and Tracing: Set up logging systems with ELK Stack, OpenTelemetry, or LangSmith to capture AI events, errors, and traces for debugging and auditing.
  • Security Implementation: Apply secure-by-design principles to protect models and data from vulnerabilities (e.g., adversarial attacks, data leakage) using tools like Adversarial Robustness Toolbox (ART).
  • System Optimization: Optimize model inference for performance (e.g., via quantization, edge deployment) and ensure compatibility with cloud (AWS, Azure) or on-premises infrastructure.
  • Collaboration: Partner with data scientists to understand model requirements, DevOps for infrastructure alignment, and stakeholders for reporting needs.
  • Testing and Validation: Perform end-to-end testing of AI integrations, including stress testing and validation of dashboard metrics.
  • Compliance: Ensure integrations comply with regulations like GDPR, HIPAA, or NIST AI RMF for secure data handling.

Minimum Qualifications
    • Education: Bachelor's or Master's degree in Computer Science, Software Engineering, Data Science, or a related field.
    • Experience:
    • 4+ years in software engineering or AI integration, with experience deploying AI models in production.
    • Hands-on experience with dashboarding tools (e.g., Grafana, Kibana) and observability platforms (e.g., Prometheus, Datadog).
    • Familiarity with cloud platforms (e.g., AWS, Azure, Google Cloud) for AI deployment.
    • Technical Skills:
    • Proficiency in Python; knowledge of JavaScript, C++, or Go is a plus for UI or system-level integration.
    • Experience with containerization (Docker, Kubernetes) and API development (REST, GraphQL).
    • Expertise in logging frameworks (e.g., ELK Stack, OpenTelemetry) and visualization tools (e.g., Plotly, Chart.js).
    • AI-Specific Skills:
    • Understanding of AI model metrics (e.g., F1 score, latency) and drift detection techniques (e.g., PSI, KS test).
    • Knowledge of AI vulnerabilities (e.g., prompt injection, model inversion) and mitigation strategies (e.g., differential privacy, ART).
    • Soft Skills:
    • Strong problem-solving skills for debugging integration issues and optimizing dashboards.
    • Excellent communication to translate technical metrics into business insights.
    • Collaboration skills to work across data science, DevOps, and product teams.
    • *Must be eligible to obtain a Department of Homeland Security EOD clearance (Requirements 1. US Citizenship, 2. Favorable Background Investigation)

Desired Qualifications
    • Experience with LLM-specific tools like LangSmith or Helicone for monitoring generative AI applications.
    • Familiarity with compliance frameworks (e.g., NIST AI RMF, OWASP AI Security Top 10).
    • Engagement with AI/ML communities, such as X platform discussions on #AISecurity or #MLOps.

About Us
Formed through the strategic union of Sev1Tech and ERT, Entarian is a premier provider of mission-critical engineering and technology solutions. Founded on a legacy of excellence dating back to 1993, Entarian is a product of an evolved and fully diversified engineering and federal technology leader. From deep space to defense and civilian missions, Entarian delivers secure, mission-aligned digital solutions that drive national resilience and operational effectiveness. We don't just support modernization; we define it.
Join the Mission and Start your Career Journey: Apply Directly via our Careers Portal Connect, Referrals & Inquiries? Email the team: careers@entarian.com
Entarian is an Equal Opportunity and Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, pregnancy, sexual orientation, gender identity, national origin, age, protected veteran status, or disability status.

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