Job Description
Job Description
Job Summary
We are seeking a highly skilled AI/ML Solutions Architect to lead the design, development, and deployment of advanced artificial intelligence and machine learning solutions supporting mission-critical government and national security programs. This role partners closely with data scientists, software engineers, cloud architects, and mission stakeholders to translate complex operational requirements into scalable, secure, and high-performance AI/ML architectures.
The ideal candidate combines deep technical expertise with a strategic mindset and has experience architecting end-to-end AI/ML solutions operating in classified cloud environments. This role spans the full ML lifecycle—from data ingestion and model training to deployment, monitoring, and governance—while ensuring compliance with DoD and Intelligence Community security standards. Strong communication skills, architectural leadership, and a commitment to secure, reliable mission outcomes are essential.
Key Responsibilities
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Architect and guide end-to-end AI/ML solutions in support of mission-critical programs
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Design, integrate, and optimize full-lifecycle ML pipelines, including data ingestion, feature engineering, model training, deployment, and monitoring
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Ensure AI/ML systems meet federal security, compliance, and accreditation requirements
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Collaborate with cross-functional technical teams and mission stakeholders to align solutions with operational needs
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Evaluate emerging AI/ML technologies and develop technical roadmaps for long-term scalability and reliability
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Support customer-facing technical engagements and clearly communicate complex AI/ML concepts to diverse audiences
Required Experience
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Bachelors degree in Computer Science, Engineering, Physics, Statistics, Mathematics, or a related field
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5+ years of professional experience in AI/ML engineering, data science, or MLOps within cloud environments
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U.S. citizenship with the ability to obtain and maintain a TS/SCI security clearance
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Demonstrated experience designing and operating end-to-end AI/ML pipelines in classified environments
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Experience operationalizing ML models and data pipelines across air-gapped, hybrid, and cloud infrastructures
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Hands-on experience with at least one major AI/ML platform (e.g., Azure Machine Learning, AWS SageMaker, Kubeflow on Kubernetes)
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Proven experience working with structured and unstructured data and managing the ML model lifecycle
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Experience collaborating with multidisciplinary teams and supporting mission stakeholders
Required Skills
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Deep knowledge of machine learning frameworks (TensorFlow, PyTorch, Scikit-learn) and data tools (Spark, Pandas, Kafka)
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Strong understanding of AI/ML architecture patterns and MLOps practices, including CI/CD, deployment, monitoring, and governance
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Proficiency in Python for AI/ML development; familiarity with Java, Go, or C++ is a plus
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Expertise with cloud-native and container technologies (Kubernetes, Docker, serverless architectures)
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Understanding of cloud security principles, zero-trust architectures, and secure system design
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Ability to translate mission requirements into technical AI/ML architectures
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Excellent written and verbal communication skills, including briefing senior stakeholders
Desired Skills
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Active TS/SCI clearance
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Professional certifications such as cloud solutions architect or AI/ML specialty certifications
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Experience with advanced ML domains (e.g., federated learning, reinforcement learning, LLM fine-tuning, vector databases, retrieval-augmented generation)
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Familiarity with DoD and Intelligence Community data environments and RMF accreditation processes
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Understanding of secure data enclaves, cross-domain solutions, and zero-trust implementations
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Experience with model interpretability, bias mitigation, and Responsible AI practices