Advanced AI Solutions Developer

1 day ago

Kanpur, Uttar Pradesh, India beBeeAgentic Full time
AI Agent Deployment Specialist

Are you an expert in Large Language Models (LLMs) and Artificial Intelligence (AI)? Do you have experience with production-grade deployment of AI agents?

Our company is seeking a skilled AI Agent Deployment Specialist to join our team. In this role, you will be responsible for designing, building, and deploying LLM-based agents and multi-modal AI applications that solve real-world business challenges.

  • Key Responsibilities:
  • 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 (Arize or similar).
  • Required Skills & Experience:
  • 5–9 years total experience, with 4+ years in NLP, CV, and LLMs.
  • Strong expertise in GenAI, LLMs, RAG pipelines, embeddings, and vector databases.
  • Proficiency in Python with strong debugging and system design skills.
  • Hands-on experience with Agentic AI frameworks (LangChain Agents, AutoGen, CrewAI, Temporal, DSPy).
  • Proven record of production-grade AI deployments (not just POCs).
  • Cloud experience: Azure (preferred), AWS, or GCP.
  • Knowledge of AI orchestration, evaluation, guardrails, and observability tools (Arize, Weights & Biases, etc.).

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