Enterprise Architect - Full Stack, AI/ML

Enterprise Architect - Full Stack, AI/ML Virginia, Richmond 01/27/2026 Contract Active Job Description: Job Summary The Enterprise Architect – Full Stack, AI/ML is responsible for defining and leading enterprise-grade architectures that integrate full stack engineering with scalable AI/ML capabilities. The role involves creating end-to-end architectures across application engineering, MLOps, cloud-native platforms, data ecosystems, and enterprise integrations. The individual will collaborate with business, product, engineering, and data science teams to deliver secure, scalable, high-performing digital ecosystems powered by AI/ML. The position requires over 12 years of hands-on and architectural experience in large-scale enterprise environments. Key Responsibilities Define full lifecycle architecture for full stack and AI/ML systems covering data management, model development, deployment, and operations. Establish enterprise architecture principles, standards, and governance for AI-enabled platforms. Drive digital modernization and cloud transformation initiatives aligned with business strategies. Evaluate and recommend emerging technologies across AI/ML, DevOps, MLOps, and cloud platforms. Architect scalable ML pipelines, automated workflows, and CI/CD–MLOps frameworks including ingestion, feature engineering, development, evaluation, deployment, and monitoring. Collaborate with data scientists and engineering teams to operationalize AI/ML models at scale. Ensure governance, compliance, versioning, reproducibility, and monitoring of ML systems. Design and review enterprise applications combining backend, frontend, cloud APIs, and microservices. Lead architecture efforts for full stack development teams including frontend, middleware, APIs, and cloud-native services. Guide teams on performance optimization, caching, distributed systems, and containerized deployments. Oversee API-first integration patterns, event-driven designs, and asynchronous architectures. Architect multi-cloud and hybrid solutions across AWS, Azure, and GCP with vendor-neutral designs. Lead cloud automation, DevOps pipelines, IaC, and observability tooling. Implement secure API management and enterprise connectivity models. Partner with business leaders to translate strategy into technical roadmaps. Mentor engineering teams on best practices for solution delivery, security, scalability, and architectural rigor. Lead architecture reviews, technical audits, and governance activities. Required Qualifications 12+ years of IT experience, including 5–7+ years in solution or enterprise architecture roles. Strong background in Java, Node.js, Python, Angular/React, REST APIs, microservices, and event-driven architecture. Experience with ML frameworks such as TensorFlow, scikit-learn, and MLlib. Expertise in data engineering, including data warehousing, ETL, metadata management, and real-time architectures. Deep knowledge of AWS, Azure, and GCP cloud services, networking, containers, Kubernetes, serverless, and distributed systems. Hands-on experience with CI/CD tools (Azure DevOps, GitHub, Jenkins) and IaC tools such as Terraform or CloudFormation. Strong leadership, communication, and problem-solving skills. Ability to drive cross-functional initiatives and influence stakeholders. Demonstrated experience delivering enterprise platforms with integrated AI/ML capabilities. Experience leading global, cross-functional, multidisciplinary teams. Preferred Qualifications Experience with enterprise-scale MLOps and federated data science operations. Experience in regulated industries such as finance, healthcare, or telecom. Certifications TOGAF Cloud architect certifications (AWS/Azure/GCP) #J-18808-Ljbffr Compunnel