Visionary GenAI Architect

7 days ago

Bareilly, Uttar Pradesh, India beBeeGenAi Full time US$ 1,50,000 - US$ 2,00,000
GenAI Specialist Position

At the forefront of technological advancements, a skilled GenAI professional is sought after to spearhead the development and deployment of production-grade projects.

The ideal candidate will possess strong expertise in Agentic AI and the ability to design, build, fine-tune, and deploy LLM agents and multi-modal AI applications with optimal performance and scalability.

Key Responsibilities:
  • Model & Agent Design:
    • Develop and implement LLM-powered agents and NLP solutions tailored to business needs, adhering to advanced design principles for structured outputs, tool usage, speculative decoding, AST-Code RAG, streaming, and async/sync processing.
    • Create multi-agent and multi-modal AI applications/frameworks, ensuring interactivity, latency optimization, failover, and usability.
  • Hands-on Coding & Development:
    • Write, test, and maintain clean, scalable, and efficient Python code for LLMs and AI agents, focusing on cost, latency, and accuracy.
    • Implement fine-tuning, embeddings, and prompt engineering, integrating models with vector databases (Milvus, Qdrant, ChromaDB, CosmosDB, MongoDB).
  • Performance & Monitoring:
    • Monitor and optimize LLM agents for latency, scalability, robustness, and explainability, implementing observability and guardrails strategies for enterprise-safe AI deployments.
    • Handle model drift, token consumption optimization, and error recovery mechanisms.
  • Research & Innovation:
    • Read, interpret, and implement AI/Agent research papers into practical production-ready solutions, staying ahead of academic and industry trends in Agentic AI, multimodal AI, orchestration frameworks, and evaluation methodologies.
    • Experiment with new AI orchestration tools, evaluation frameworks, and observability platforms (Arize or similar).
  • Debugging & Issue Resolution:
    • Diagnose and resolve model inaccuracies, system integration issues, and performance bottlenecks, applying advanced debugging techniques to troubleshoot deployment errors, data inconsistencies, and unexpected agent behaviors.
  • Continuous Learning & Adaptability:
    • Quickly unlearn outdated practices and adapt to emerging GenAI and Agentic AI technologies, contributing to a culture of innovation by experimenting, prototyping, and scaling cutting-edge AI solutions.

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