Overview:
VTG is seeking a highly experienced and innovative AI Architect to lead the design, development, evaluation, and deployment of advanced artificial intelligence solutions in support of mission-critical and enterprise initiatives. This role requires deep expertise in modern AI/ML architectures, including agentic AI systems, large language models (LLMs), autonomous workflows, AI evaluation frameworks, and production-grade machine learning operations (MLOps). This position is located in Chantilly, VA.
The ideal candidate is both technically exceptional and customer-facing — capable of advising senior leadership, engaging directly with government and commercial stakeholders, and serving as a trusted authority on emerging AI technologies and best practices. This individual must have hands-on experience building and operationalizing AI systems at scale and possess a strong understanding of modern AI governance, responsible AI principles, and evaluation methodologies.
Responsibilities:
Architect, design, and implement advanced AI/ML solutions, including:
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Agentic AI systems
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Retrieval-Augmented Generation (RAG)
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Large Language Model (LLM) integrations
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Autonomous and semi-autonomous workflows
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AI orchestration frameworks
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Predictive analytics and traditional ML models
Lead the end-to-end AI lifecycle, including:
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Data ingestion and preparation
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Model development and fine-tuning
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AI testing and evaluation
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Model deployment and monitoring
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Operational sustainment and optimization
Develop and mature AI evaluation and testing methodologies, including:
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Traditional ML evaluation metrics
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LLM benchmarking
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Red teaming and adversarial testing
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Hallucination detection
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Bias and fairness assessments
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Performance and reliability testing
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Human-in-the-loop evaluation strategies
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Design scalable MLOps and AIOps pipelines to support secure and repeatable deployment of AI capabilities in enterprise and cloud environments
Establish and implement AI governance frameworks, including:
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Responsible AI practices
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Security and compliance controls
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Model transparency and explainability
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Risk management
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Data governance standards
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Serve as a senior technical advisor to customers, executives, and program leadership on AI strategy, architecture, modernization, and emerging capabilities.
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Lead technical discussions, architecture reviews, demonstrations, and customer briefings with confidence and authority.
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Stay current with emerging AI research, industry trends, open-source technologies, and commercial AI platforms; continuously assess applicability to organizational and customer needs.
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Mentor engineers, data scientists, and software developers on AI best practices, architectures, and implementation strategies.
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Collaborate across engineering, cybersecurity, cloud, data, and product teams to deliver integrated AI solutions.
Qualifications:
Required Qualifications:
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Bachelor’s degree in Computer Science, Artificial Intelligence, Data Science, Software Engineering, Mathematics, or related technical field.
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Master’s degree or PhD preferred.
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10–15+ years of experience in artificial intelligence, machine learning, software engineering, data engineering, or related technical disciplines.
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Demonstrated experience architecting and deploying enterprise-scale AI/ML solutions in production environments.
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Hands-on experience building and operationalizing:
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Agentic AI systems
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LLM-powered applications
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AI orchestration frameworks
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Autonomous decision-support systems
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Strong understanding of:
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Machine learning algorithms
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Deep learning techniques
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Natural language processing (NLP)
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Reinforcement learning concepts
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Statistical modeling and AI evaluation methodologies
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Experience with AI testing, validation, benchmarking, and evaluation frameworks for both traditional ML and generative AI systems.
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Experience implementing practical MLOps pipelines and AI operationalization frameworks.
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Strong programming experience with:
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Python
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Jupyter Notebooks or equivalent notebook environments
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Experience with big data and distributed processing technologies such as:
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Apache Spark
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Databricks (preferred)
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Experience with one or more major cloud platforms:
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Microsoft Azure
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Amazon Web Services (AWS)
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Google Cloud Platform (GCP)
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Familiarity with:
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Vector databases
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AI orchestration frameworks (LangChain, Semantic Kernel, CrewAI, AutoGen, etc.)
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Containerization and orchestration technologies
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CI/CD pipelines for AI deployments
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Strong communication and presentation skills with demonstrated customer-facing experience.
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Ability to translate complex technical concepts into actionable business and mission solutions.
Preferred Qualifications:
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Experience supporting Federal Government, DoD, Intelligence Community, or highly regulated environments.
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Experience implementing secure AI architectures in classified or sensitive environments.
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Familiarity with AI security, adversarial AI, and zero trust principles.
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Experience with GPU infrastructure, model optimization, and scalable inference architectures.
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Published research, conference presentations, patents, or contributions to the AI community preferred.
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Active participation in AI research communities, industry working groups, or open-source AI initiatives.
Clearance Requirement
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Active Secret security clearance required, or ability to obtain and maintain a Secret clearance.
Desired Characteristics
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Strategic thinker with strong technical depth and hands-on engineering capability.
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Passion for continuous learning and staying ahead of rapidly evolving AI technologies.
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Comfortable operating in ambiguous and fast-paced technical environments.
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Strong leadership, collaboration, and mentoring abilities.
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Customer-focused with executive presence and consultative communication skills.
Technologies & Tools
Experience with several of the following is desired:
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Python
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Jupyter Notebook
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Apache Spark
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Databricks
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TensorFlow
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PyTorch
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Hugging Face
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LangChain
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Semantic Kernel
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CrewAI
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AutoGen
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Kubernetes
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Docker
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Azure AI Services
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AWS SageMaker
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Google Vertex AI
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Vector databases
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MLflow
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GitLab/GitHub CI/CD pipelines
Work Environment
This role may support hybrid, on-site, or customer-location work environments depending on program requirements. Occasional travel may be required for customer engagement, technical workshops, or industry events.
