AI Systems Architect

We are seeking an experienced AI Systems Architect to design, build, and scale high-performance distributed AI systems. The ideal candidate will have deep expertise in GenAI, LLMs, and cloud-native architectures, along with hands-on experience in building enterprise-scale AI/ML platforms and agent-based systems., * Architect and deliver scalable, high-performance distributed systems

• Design and deploy AI/ML and GenAI platforms at enterprise scale
• Build and manage agent-based architectures, including:
• Prompt and context engineering
• MCP servers
• Evaluation frameworks
• Optimize LLM inference pipelines for latency, throughput, and efficiency
• Design and implement agent data & retrieval systems (vector DBs, hybrid search, memory, graph-based reasoning)
• Lead Kubernetes-based, cloud-native deployments
• Provide technical leadership, architecture governance, and hands-on mentoring to engineering teams

• Strong experience in designing and implementing high-performance, large-scale distributed systems
• Proven experience in implementing and deploying AI/ML platforms at scale
• Expertise in building agent-based architectures, evaluation frameworks, and prompt/context engineering
• Knowledge of MCP (Model Context Protocol) servers
• Hands-on experience in LLM inference optimization, including batching and caching strategies
• Strong experience with Kubernetes and cloud infrastructure (AWS/Azure/GCP)
• Proficiency in at least one programming language (Python, Java, Go, etc.)
• Expertise in designing agent data stacks & retrieval systems, including:
• Vector databases
• Hybrid search
• Data freshness strategies
• Memory systems
• Graph reasoning
• BM25 and advanced retrieval techniques, * Experience with RAG (Retrieval-Augmented Generation) frameworks
• Familiarity with multi-agent systems and orchestration frameworks
• Exposure to real-time data pipelines and streaming architectures