Senior AI Engineer

9 hours ago

Mysore, Karnataka, India beBeeAgentic Full time ₹ 10,00,000 - ₹ 15,00,000
AI Engineering Professional

We are seeking a skilled AI engineering professional with extensive experience in large-scale AI project deployment, strong expertise in agentic AI, and proficiency in NLP, Computer Vision, and LLM-based systems.

This role involves designing, building, fine-tuning, and deploying production-grade LLM agents and multi-modal AI applications that address real-world business challenges. You will play a key role in shaping agent design, orchestration, and observability, ensuring enterprise-grade scalability, robustness, and performance.

Key Responsibilities:

  • Agent Design and Development: 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.
  • Coding and Maintenance: 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 and Optimization: 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 and 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 and 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  • Continuous Learning and Adaptability: Quickly unlearn outdated practices and adapt to emerging GenAI and Agentic AI technologies.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.

Required Skills and 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.

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