Enterprise GenAI Architect

Enterprise GenAI Architect
Position Overview
We are seeking an experienced Enterprise GenAI Architect to assess, strengthen, and scale an enterprise AI platform environment. The ideal candidate will bring strong expertise in Generative AI architecture, cloud platforms, enterprise integration, security, governance, and production readiness.
This role will work closely with engineering, infrastructure, security, and business stakeholders to review the existing AEGIS AI platform, identify architectural gaps, and define a scalable and secure roadmap for enterprise adoption.
Key Responsibilities

• Assess and review the existing AEGIS AI platform architecture and identify opportunities for improvement.

• Drive production readiness, platform hardening, scalability, and operational stability.

• Define enterprise integration strategies and migration roadmaps.

• Design scalable, secure, highly available AI platform architectures.

• Partner with engineering teams to resolve architectural, performance, integration, and scaling challenges.

• Establish best practices for monitoring, observability, security, governance, and production support.

• Define architecture standards for integrating AI capabilities with enterprise applications and APIs.

• Create technical architecture documentation, implementation plans, and modernization roadmaps.

• Support cloud infrastructure optimization, performance improvement, and cost-efficiency initiatives.

• Provide architectural guidance to engineering, DevOps, security, and platform teams.

Required Qualifications

• 20+ years of overall IT experience, including significant experience in enterprise or solution architecture.

• Strong hands-on experience with Generative AI, AI platforms, and enterprise AI architecture.

• Experience designing and implementing scalable enterprise AI solutions.

• Strong knowledge of AWS and/or Microsoft Azure.

• Experience with Docker, Kubernetes, and containerized application environments.

• Strong understanding of REST APIs, API integration, microservices, and enterprise systems integration.

• Knowledge of enterprise security, governance, access controls, compliance, and production support.

• Experience working with distributed, scalable, and highly available application architectures.

• Strong technical documentation and architecture roadmap development skills.

• Excellent communication, stakeholder management, and cross-functional collaboration skills.

Preferred Qualifications

• Experience implementing enterprise-scale Generative AI or LLM solutions.

• Knowledge of MLOps, AI platform operations, model deployment, and monitoring.

• Experience with CI/CD pipelines, DevOps practices, and infrastructure automation.

• Familiarity with cloud-native AI services and AI/ML platform ecosystems.

• Experience supporting AI platforms through production deployment, optimization, and operational maturity.