Principle Architect

Key Responsibilities

• Architect and deliver scalable, high-performance distributed systems.
• Design and deploy AI/ML and GenAI platforms at enterprise scale.
• Build agent-based architectures, including prompt/context engineering, MCP servers, and evaluation frameworks.
• Optimize LLM inference pipelines (batching, caching, latency, throughput).
• Design agent data & retrieval stacks (vector DBs, hybrid search, memory, graphs).
• Lead Kubernetes-based, cloud-native deployments.
• Provide technical leadership, architecture governance, and hands-on guidance.

Requirements

• Experience in designing and implementing high-performance, large-scale distributed systems.
• Implementing and Deploying AI/ML platforms at scale.
• Building and Creating agent architectures, know-how of prompt/context engineering, MCP servers.
• Hands-on experience in LLM inference optimization, batching and caching strategies.
• Strong in any programming language.
• Expertise in designing agent data stack & retrieval systems (vector dbs, hybrid search, data freshness, memory, graph reasoning, BM25 etc).