Advanced AI Expertise Specialist

5 days ago

Salem, Tamil Nadu, India beBeeGenaicist Full time ₹ 2,00,00,000 - ₹ 2,50,00,000
Job Description

As a cutting-edge GenAI professional, you will play a pivotal role in shaping the design and deployment of production-grade Large Language Model (LLM) agents and multi-modal AI applications.

With expertise in Natural Language Processing (NLP), Computer Vision, and LLM-based agentic systems, you will work on conceptualizing, designing, and implementing LLM-powered agents and NLP solutions tailored to business needs.

The ideal candidate will have experience with Agentic AI frameworks such as LangChain Agents, AutoGen, CrewAI, Temporal, and DSPy. You will also be proficient in Python with strong debugging and system design skills. A proven record of production-grade AI deployments is essential, along with cloud experience in Azure, AWS, or GCP.

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 such as Milvus, Qdrant, ChromaDB, CosmosDB, and 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 like Arize.
  • 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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