AI Solutions Architect

6 days ago


Hubli, Karnataka, India beBeeGenAI Full time ₹ 1,50,00,000 - ₹ 2,01,00,000

Are you a skilled technologist passionate about developing cutting-edge GenAI solutions?

Job Overview:

We are seeking an experienced professional to join our team as a GenAI expert.

Key Responsibilities:
  • GenAI Solution Design
    • Design and develop innovative GenAI solutions for real-world business challenges.
    • Build and deploy production-grade LLM agents and multi-modal AI applications.
    • Apply advanced design principles for structured outputs, tool usage, and latency optimization.
  • Coding & Development
    • Write 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).
  • Performance Monitoring
    • Monitor and optimize LLM agents for latency, scalability, and robustness.
    • 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, and orchestration frameworks.
    • Experiment with new AI orchestration tools and evaluation methodologies.
  • Debugging Issue Resolution
    • Diagnose and resolve model inaccuracies, system integration issues, and performance bottlenecks.
    • Apply advanced debugging techniques to troubleshoot deployment errors and data inconsistencies.
  • Continuous Learning Adaptability
    • Quickly adapt to emerging GenAI and Agentic AI technologies.
    • Contribute to a culture of innovation by experimenting, prototyping, and scaling cutting-edge AI solutions.
    Requirements:
    • 5–9 years of total experience, with 4+ years in NLP, CV, and LLMs.
    • Strong expertise in GenAI, LLMs, RAG pipelines, embeddings, and vector databases.
    • Proficiency in Python, hands-on experience with Agentic AI frameworks, and proven record of production-grade AI deployments.


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