Enterprise Architect - Full Stack, AI/ML Role Overview

Enterprise Architect - Full Stack, AI/MLRole Overview<br /> The Enterprise Architect - Full Stack, AI/ML will be responsible for defining and leading enterprise grade solution architectures that integrate modern full stack engineering practices with scalable AI/ML capabilities. The role requires deep experience across application engineering, MLOps, cloud-native architectures, data engineering, and enterprise integration.<br /> You will work closely with business, product, engineering, and data science teams to conceptualize, architect, and deliver complex, secure, scalable, and high performing digital ecosystems powered by AI/ML.<br /> <br /> This role requires 12+ years of hands-on and architectural experience in large-scale enterprise environments.<br /> Key Responsibilities<br /> 1. Enterprise Architecture & Strategy<br /> Define end to end architecture for full stack and AI/ML systems across discovery, data management, model development, deployment, and operations.<br /> Establish enterprise architecture principles, standards, and governance models for AI-enabled platforms.<br /> Drive digital modernization and cloud transformation initiatives aligned with business goals.<br /> Evaluate emerging technologies (AI/ML, DevOps, MLOps, cloud platforms) to accelerate enterprise innovation.<br /> <br /> 2. AI/ML Solution Architecture<br /> Architect scalable ML pipelines, automated workflows, CI/CD & MLOps frameworks (data ingestion feature engineering model development evaluation deployment monitoring).<br /> Work with data scientists, ML engineers, and analytics engineers to operationalize AI/ML models at scale.<br /> Ensure governance, compliance, versioning, reproducibility, and monitoring for AI/ML systems.<br /> <br /> 3. Full Stack & Platform Architecture<br /> Design and review enterprise applications combining backend, frontend, cloud APIs, and microservices.<br /> Lead architecture for full stack development teams including scalable frontend, middleware, data APIs, microservices, and cloud-native services.<br /> Guide solution teams on performance optimization, caching, distributed systems, and containerized deployments (Docker/K8s).<br /> Oversee API-first integration patterns, event-driven designs, and asynchronous architectures.<br /> <br /> 4. Cloud & DevOps/MLOps Integration<br /> Architect multi cloud and hybrid solutions across AWS, Azure, and GCP ensuring interoperability and vendor neutral design. (Patterns similar to Carelon Apigee Architect content on multi cloud design). [Carelon Ap...Architect | Word]<br /> Lead cloud automation, DevOps pipelines, infrastructure as code, and observability tooling.<br /> Implement secure, robust API management and enterprise connectivity models.<br /> <br /> 5. Stakeholder Leadership & Governance<br /> Partner with business leaders to translate complex business goals into technical roadmaps.<br /> Mentor engineering teams and foster best practices in solution delivery, coding, security, scalability, and architecture rigor.<br /> Facilitate architecture review boards, technical audits, and solution governance.<br /> <br /> Required Skills & Experience<br /> Technical Expertise<br /> Full Stack Engineering:<br /> <br /> Strong background in Java, Node.js, Python, Angular/React, REST APIs, microservices, event-driven architecture. (Aligned with similar roles like Java Architect / Full Stack Developer).<br /> AI/ML Engineering:<br /> <br /> Experience with ML frameworks (TensorFlow, scikit learn, MLlib), feature engineering, pipeline automation, monitoring, and operational ML.<br /> Cloud & Platform Architecture:<br /> <br /> Deep knowledge of AWS/Azure/GCP, cloud networking models, containers (Docker), Kubernetes, serverless, and distributed systems.<br /> Data Engineering:<br /> <br /> Strong understanding of data warehousing concepts, ETL frameworks, governance, metadata management, and real time data architectures.<br /> DevOps/MLOps:<br /> <br /> CI/CD (Azure DevOps, GitHub, Jenkins), model deployment automation, IaC (Terraform/CloudFormation).<br /> <br /> Soft Skills<br /> Excellent leadership, problem solving, and communication skills fit for enterprise architect roles.<br /> Ability to drive cross functional initiatives and influence without authority.<br /> Strong stakeholder management, negotiation, and architectural storytelling abilities.<br /> <br /> Experience<br /> 12+ years of IT experience, including:<br /> 5-7+ years in solution or enterprise architecture roles.<br /> Demonstrated delivery of large-scale enterprise platforms with AI/ML components.<br /> Experience leading global, cross functional, multi disciplinary teams.<br /> <br /> <br /> <br /> Preferred Qualifications<br /> Certifications: TOGAF, cloud architect certifications, AI/ML specialization.<br /> Experience with enterprise-scale MLOps & federated data science operations<br /> Background in regulated industries (finance, healthcare, telecom) is a plus.<br /> <br /> Notes - Enterprise Architect Full stack, AI/ML<br /> <br /> Mandatory Skills - fullstack,cloud-native architecture,enterprise architecture,full stack engineering,ai/ml,application engineering,mlops