Systems Architect

Senior AI Systems ArchitectUnissant, Inc. delivers innovative capabilities to the agencies that keep our nation healthy and safe. We apply our domain expertise, data acumen, and technology know-how to achieve breakthrough results for our clients. Working collaboratively, we advance missions and careers through a focus on honesty, integrity, and dependability. We continuously look for talent, excited to join that effort. To learn more about our exciting organization, please visit us at are seeking a Senior AI Systems Architect to serve as a technical lead and enterprise architect for Artificial Intelligence (AI), Machine Learning (ML), Generative AI (Gen-AI), and advanced analytics initiatives supporting our federal customer. This role is responsible for designing, operationalizing, and scaling secure, mission-focused AI capabilities that enhance customer's AI/ML services, image analysis, anomaly detection, operational intelligence, and decision-support missions.Position Overview:The Senior AI Systems Architect leads 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. The role combines enterprise architecture, AI engineering, cloud modernization, cybersecurity, and mission operations expertise to deliver scalable, secure, and governable AI solutions aligned with operational requirements and federal AI governance mandates.This position serves as a trusted technical advisor to leadership, program stakeholders, architects, developers, data scientists, and cybersecurity teams while driving the transition of AI capabilities from research and experimentation into production operational environments.Essential Duties and Responsibilities:Enterprise AI Architecture & StrategyServe as the lead architect for AI and Gen-AI initiatives supporting operational mission requirements across national security customer domains.Design and operationalize enterprise AI architectures supporting scalable AI-as-a-Service capabilities across client applications.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.Define enterprise AI integration patterns supporting cloud-native, event-driven, and microservices-based architectures.AI/ML & Gen-AI Solution EngineeringLead design and deployment of AI/ML and Gen-AI solutions including:RAG architecturesAgentic AI frameworksLLM orchestrationComputer VisionImage analysis and object detectionAnomaly detectionPredictive analyticsNLP and summarization servicesIntelligent search and semantic retrievalDesign scalable pipelines for AI model training, inference, monitoring, retraining, and operational management.Implement secure Gen-AI guardrails addressing:Hallucination mitigationPrompt injection preventionPrompt leakage controlsExplainability and traceabilityResponsible AI governanceArchitect high-throughput AI processing frameworks capable of supporting near real-time mission operations and large-scale analytical workloads.Mission Systems Integration & ModernizationIntegrate AI services into operational systems, mission workflows, and enterprise data platforms.Architect event-driven data ecosystems leveraging Kafka/MSK, APIs, streaming pipelines, and real-time interoperability frameworks.Support modernization of legacy systems and data platforms into scalable cloud-native AI-enabled architectures.Design interoperable data frameworks leveraging NIEM, WCO, JSON/REST APIs, and other federal interoperability standards.Enable AI integration across structured and unstructured mission datasets including operational intelligence, targeting data, image repositories, and external partner feeds.Cloud, MLOps & DevSecOpsArchitect secure AI environments leveraging AWS and Google cloud ecosystems including:Amazon BedrockAWS SageMakerVertex AIDatabricksContainerized AI platformsImplement Infrastructure as Code (IaC), automated provisioning, CI/CD, and MLOps pipelines supporting rapid AI deployment and lifecycle management.Design AI operationalization pipelines with:Automated model deploymentDrift monitoringRetraining triggersModel governanceSecurity automationCollaborate with DevSecOps and cybersecurity teams to integrate AI solutions into secure enterprise delivery pipelines.Security, Governance & ComplianceEnsure all AI architectures comply with:DHS security policiesNIST 800-series standardsRMF requirementsZero Trust principlesFederal AI governance guidelinesArchitect secure data access, role-based controls, encryption, audit logging, and AI activity monitoring.Support ATO processes and system security documentation for AI-enabled solutions.Establish governance frameworks for AI model validation, testing, explainability, and operational accountability.Innovation & ResearchCollaborate with customer, cloud providers, academic institutions, and emerging technology partners to evaluate and operationalize innovative AI capabilities.Lead technical evaluations, proof-of-concepts, and pilot initiatives for emerging AI technologies.Research and operationalize advanced AI capabilities including:Agentic AIMultimodal AIFederated AISynthetic data generationMassive parallel AI processingAI-enabled image intelligenceSupport the expansion of CBP's Technology Reference Model (TRM) for AI technologies and tools.Technical Leadership & Stakeholder EngagementProvide technical leadership and mentorship to AI engineers, data scientists, architects, and development teams.Lead architecture reviews, technical strategy sessions, and solution design workshops.Translate operational mission requirements into scalable technical architectures and implementation roadmaps.Develop technical white papers, executive briefings, architecture diagrams, and implementation strategies for leadership.Support proposal development, technical volume writing, and customer demonstrations for customer's AI initiatives.Work Experience and Job Skills:Required: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.Strong expertise in:Generative AILLM architecturesRAG frameworksMLOpsAI operationalizationComputer VisionNLPCloud-native architecturesExperience with AWS and/or Google Cloud AI ecosystems.Strong experience designing:Event-driven architecturesAPI ecosystemsData streaming platformsMicroservices architecturesEnterprise integration frameworksExperience 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