Role & responsibilities

- Design scalable and reusable AI/GenAI platform architectures supporting multiple teams and enterprise use cases.
- Architect distributed AI systems with solid 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