Enterprise Architect

Job Description: The Enterprise Architect will define and govern end-to-end enterprise architecture for full stack and AI/ML platforms. This role drives digital modernization, cloud transformation, and scalable AI-enabled solutions while partnering closely with business and engineering leadership. Responsibilities: Enterprise Architecture And Strategy: Define end-to-end architecture for full stack and AI/ML systems across Client, data management, model development, deployment, and operations. Establish enterprise architecture principles, standards, and governance models for AI-enabled platforms. Drive digital modernization and cloud transformation initiatives aligned with business goals. Evaluate emerging technologies including AI/ML, DevOps, MLOps, and cloud platforms to accelerate enterprise innovation. AI/ML Solution Architecture: rchitect scalable ML pipelines, automated workflows, CI/CD pipelines, and MLOps frameworks covering data ingestion, feature engineering, model development, evaluation, deployment, and monitoring. Collaborate with data scientists, ML engineers, and analytics engineers to operationalize AI/ML models at scale. Ensure governance, compliance, versioning, reproducibility, and monitoring of AI/ML systems. Full Stack And Platform Architecture: Design and review enterprise applications across backend, frontend, cloud APIs, and microservices. Lead architecture for full stack development teams including frontend, middleware, data APIs, microservices, and cloud-native services. Guide teams on performance optimization, caching strategies, distributed systems, and containerized deployments using Docker and Kubernetes. Oversee API-first integration patterns, event-driven designs, and asynchronous architectures. Cloud And DevOps/MLOps Integration: rchitect multi-cloud and hybrid solutions across AWS, Azure, and GCP ensuring interoperability and vendor-neutral design. Lead cloud automation, DevOps pipelines, infrastructure as code, and observability tooling. Implement secure and scalable API management and enterprise connectivity models. Stakeholder Leadership And Governance: Partner with business leaders to translate business objectives into technical roadmaps. Mentor engineering teams and promote best practices in coding, security, scalability, and architectural rigor. Facilitate architecture review boards, technical audits, and solution governance activities. Requirement/Must Have: Strong background in full stack engineering including Java, Node.js, Python, Angular or React, REST APIs, microservices, and event-driven architecture. Hands-on experience with AI/ML frameworks such as TensorFlow, Scikit-learn, and MLlib. Deep knowledge of cloud platforms including AWS, Azure, and GCP. Strong experience with containers, Kubernetes, serverless architectures, and distributed systems. Expertise in CI/CD pipelines, DevOps, MLOps, and infrastructure as code using Terraform or CloudFormation. Experience: 12+ years of overall IT experience. 5-7+ years of experience in solution or enterprise architecture roles. Proven delivery of large-scale enterprise platforms with AI/ML components. Experience leading global, cross-functional, and multi-disciplinary teams. Skills: Full stack architecture and engineering. I/ML platform design and MLOps. Cloud and hybrid architecture. Data engineering and real-time data platforms. DevOps, CI/CD, and automation. Should Have: TOGAF certification. Cloud architect certifications. I/ML specialization certifications. Experience with enterprise-scale MLOps and federated data science operations. Background in regulated industries such as finance, healthcare, or telecom. Qualification And Education: Bachelor's degree in Computer Science, Engineering, or related field, or equivalent work experience.

Created: 2026-03-04