Openkyber - Multi Cloud Networking Engineer

AI Developer is needed in Georgia, United States.

Client: Openkyber

Location: Georgia

Contract: undefined

Job Description

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. 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. This role requires 12+ years of hands-on and architectural experience in large-scale enterprise environments.

Key Responsibilities

• Define end-to-end architecture for full stack and AI/ML systems across discovery, 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 (AI/ML, DevOps, MLOps, cloud platforms) to accelerate enterprise innovation.
• Architect scalable ML pipelines, automated workflows, CI/CD & MLOps frameworks.
• Ensure governance, compliance, versioning, reproducibility, and monitoring for AI/ML systems.
• Design and review enterprise applications combining backend, frontend, cloud APIs, and microservices.
• Lead architecture for full stack development teams including scalable frontend, middleware, data APIs, microservices, and cloud-native services.
• Guide solution teams on performance optimization, caching, distributed systems, and containerized deployments (Docker/K8s).
• Oversee API-first integration patterns, event-driven designs, and asynchronous architectures.
• Architect multi-cloud and hybrid solutions across AWS, Azure, and GP ensuring interoperability and vendor neutral design.
• Lead cloud automation, DevOps pipelines, infrastructure as code, and observability tooling.
• Implement secure, robust API management and enterprise connectivity models.
• Partner with business leaders to translate complex business goals into technical roadmaps.
• Mentor engineering teams and foster best practices in solution delivery, coding, security, scalability, and architecture rigor.
• Facilitate architecture review boards, technical audits, and solution governance.

Required Skills & Experience

• Strong background in Java, Node.js, Python, Angular/React, REST APIs, microservices, event-driven architecture.
• Experience with ML frameworks (TensorFlow, scikit learn, MLlib), feature engineering, pipeline automation, monitoring, and operational ML.
• Deep knowledge of AWS/Azure/GP, cloud networking models, containers (Docker), Kubernetes, serverless, and distributed systems.
• Strong understanding of data warehousing concepts, ETL frameworks, governance, metadata management, and real-time data architectures.
• Experience with CI/CD (Azure DevOps, GitHub, Jenkins), model deployment automation, IaC (Terraform/CloudFormation).
• Excellent leadership, problem-solving, and communication skills.
• Ability to drive cross-functional initiatives and influence without authority.
• Strong stakeholder management, negotiation, and architectural storytelling abilities.

Experience

12+ years of IT experience, including: 5-7+ years in solution or enterprise architecture roles. Demonstrated delivery of large-scale enterprise platforms with AI/ML components. Experience leading global, cross-functional, multi-disciplinary teams.

Preferred Qualifications

• Certifications: TOGAF, cloud architect certifications, AI/ML specialization.
• Experience with enterprise-scale MLOps & federated data science operations.
• Background in regulated industries (finance, healthcare, telecom) is a plus.

Mandatory Skills

Fullstack, Cloud-native architecture, enterprise architecture, fullstack engineering, AI/ML, application engineering and MLOps.