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
* Architect scalable ML pipelines, automated workflows, CI/CD pipelines, 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
* Architect 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.
* AI/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.
* AI/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.
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