AI Strategist

6 days ago

Delhi, Delhi, India beBeeInnovation Full time ₹ 40,00,000 - ₹ 45,00,000

Artificial Intelligence Architect

As an Artificial Intelligence Architect at a leading organization, you will play a pivotal role in shaping the future of AI and Machine Learning (ML).

About the Role

We are seeking an experienced expert to join our team. The ideal candidate will have strong expertise in Natural Language Processing (NLP), Computer Vision, and Large Language Model (LLM) based agentic systems.

Key Responsibilities
  • Model & Agent Design:
    • 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    • Quickly unlearn outdated practices and adapt to emerging GenAI and Agentic AI technologies.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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