Senior AI Systems Architect
On-siteAshburn, Virginia, United States
Job Summary
Lead the design of enterprise AI ecosystems and reusable AI services within the client's AI Enablement Center, enabling AI-as-a-Service capabilities across multiple applications and operational environments. Develop reusable AI frameworks, shared services, and reference architectures aligned with customer enterprise standards and governance models. Architect multimodal AI solutions supporting text, image, video, and structured/unstructured data analysis, including RAG, agentic frameworks, and computer vision. Design scalable pipelines for AI model training, inference, monitoring, and retraining while implementing secure Gen-AI guardrails for hallucination mitigation and prompt injection prevention. Integrate AI services into operational systems and mission workflows, leveraging event-driven data ecosystems and cloud-native architectures on AWS and Google Cloud. Provide technical leadership to engineers and architects, translating mission requirements into scalable roadmaps and supporting proposal development and customer demonstrations for federal government clients.
Required Qualifications
- 12+ years of experience in enterprise architecture, AI/ML engineering, cloud modernization, or advanced analytics solutions
- 5+ years designing and implementing AI/ML or Gen-AI solutions in enterprise or federal environments
- Bachelor's Degree in Computer Science, Information Technology Management or Engineering
- Active TS or CBP BI
- Strong expertise in Generative AI
- Strong expertise in LLM architectures
- Strong expertise in RAG frameworks
- Strong expertise in MLOps
- Strong expertise in AI operationalization
- Strong expertise in Computer Vision
- Strong expertise in NLP
- Strong expertise in Cloud-native architectures
- Experience with AWS and/or Google Cloud AI ecosystems
- Strong experience designing Event-driven architectures
- Strong experience designing API ecosystems
- Strong experience designing Data streaming platforms
- Strong experience designing Microservices architectures
- Strong experience designing Enterprise integration frameworks
- Experience implementing secure AI and DevSecOps pipelines within regulated environments
- Strong understanding of federal cybersecurity and compliance frameworks including NIST RMF and Zero Trust
- Experience operationalizing AI-as-a-Service capabilities across mission applications
- Experience designing scalable multimodal AI platforms supporting image intelligence, semantic search, and automated metadata generation
- Experience reducing operational analytical processing times from hours/days to near real-time through the implementation of massively parallel AI architectures
- Experience implementing secure AI governance and operationalization frameworks aligned with customer AI policies and federal security mandates
- Experience enabling reusable enterprise AI services to accelerate adoption of AI across operational domains
Desired Qualifications
- MBA/Master's Degree in a relevant field of study
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