Artificial Intelligence Architect

Role & responsibilities

• Design scalable and reusable AI/GenAI platform architectures supporting multiple teams and enterprise use cases.
• Architect distributed AI systems with strong focus on scalability, reliability, performance, security, and production readiness.
• Design and implement APIs, reusable platform components, and AI services for enterprise adoption.
• Establish AI quality, evaluation, observability, telemetry, and monitoring frameworks.
• Develop platform capabilities for LLM/GenAI applications, including grounding, retrieval, memory, context management, and production hardening.
• Define tool/agent registry and private registry patterns for enterprise AI platforms.
• Build reference architectures, accelerators, and reusable frameworks to drive AI adoption across teams.
• Work with cloud ML platforms and MLOps teams to operationalize AI/ML solutions.
• Guide engineering teams on architecture, design standards, reliability, and AI best practices.
• Ensure enterprise AI solutions meet appropriate security, governance, compliance, and operational standards.

Preferred candidate profile

• AI Platform Architecture
• Generative AI / LLM Architecture
• API Design
• Distributed Systems
• Reliability Engineering / SRE
• AI Quality & Evaluation
• AI Telemetry / Observability / Monitoring
• Experience building reusable AI platform components used across multiple teams
• Production experience with large-scale AI systems

Education

Master's degree in Computer Science, Computer Engineering, Technology, Information Systems, Engineering, or related technical discipline is preferred. Equivalent experience may be considered.