Role & responsibilities
Design scalable and reusable AI/GenAI platform architectures supporting multiple teams and enterprise use cases.
Architect distributed AI systems with robust 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.

📌 Artificial Intelligence Architect Hyderabad
🏢 Elabs Infotech
📍 Hyderabad