Senior Artificial Intelligence Architect

2 weeks ago

Ajmer, Rajasthan, India beBeeGenaicist Full time ₹ 19,50,000 - ₹ 25,40,000

We are seeking a highly skilled AI professional to join our organization. As a key member, you will be responsible for designing, building, and deploying production-grade LLM agents and multi-modal AI applications that solve real-world business challenges.

About the Role

We are looking for an individual with strong experience in NLP, Computer Vision, and LLM-based agentic systems. In this role, you will play a key part in shaping agent design, orchestration, and observability, ensuring enterprise-grade scalability, robustness, and performance.

Key Responsibilities:

  • Model & Agent Design: Conceptualize, design, and implement LLM-powered agents and NLP solutions tailored to business needs.
  • Build multi-agent and multi-modal AI applications/frameworks, ensuring interactivity, latency optimization, failover, and usability.
  • Apply advanced design principles for structured outputs, tool usage, speculative decoding, AST-Code RAG, streaming, and async/sync processing.
  • Hands-on Coding & Development: Write, test, and maintain clean, scalable, and efficient Python code for LLMs and AI agents.
  • Implement fine-tuning, embeddings, and prompt engineering with a focus on cost, latency, and accuracy.
  • Integrate models with vector databases (Milvus, Qdrant, ChromaDB, CosmosDB, MongoDB).
  • Performance & Monitoring: Monitor and optimize LLM agents for latency, scalability, robustness, and explainability.
  • Implement 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.
  • Stay 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.
  • Debugging & Issue Resolution: Diagnose and resolve model inaccuracies, system integration issues, and performance bottlenecks.
  • Apply 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  • Continuous Learning & Adaptability: Quickly unlearn outdated practices and adapt to emerging GenAI and Agentic AI technologies.
  • Contribute to a culture of innovation by experimenting, prototyping, and scaling cutting-edge AI solutions.

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