LLM Engineer

• Design structured reasoning pipelines, planning flows, chain-of-thought workflows
• Build capability primitives such as memory, personalization, proactive insights
• Develop modular and reusable intelligence components
• Lead the design and deployment of LLM-based product functionality
• Ensure output reliability, consistency, safety, and user-centric alignment
• Apply prompting, constraints, and reasoning structures to reduce hallucination
• Build and optimize multi-hop, multi-source retrieval pipelines
• Implement chunking, indexing, reranking, and retrieval evaluation
• Ensure RAG improves factuality and reduces error rates
• Select appropriate model families based on capability and cost constraints
• Develop routing logic for hybrid model usage
• Collaborate with engineering to optimize latency, cost, and scalability
• Define evaluation frameworks and monitoring pipelines
• Troubleshoot production issues and lead algorithm-level improvements

LLM Algorithm Tech Lead – Applied Large Language Model Systems

Operator-In-Residence, AI Infrastructure, Software

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