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▷ Apply in 3 Minutes : GenAI professional -Agentic AI

▷ Apply in 3 Minutes : GenAI professional -Agentic AI

Grid DynamicsIndia
1 day ago
Job description

We are Hiring GenAI professional with proven production-grade project deployment experience with strong expertise in Agentic AI.

About the Role

We are looking for a GenAI professional with strong experience in NLP, Computer Vision, and LLM-based agentic systems. In this role, you will design, build, fine-tune, and deploy production-grade LLM agents and multi-modal AI applications that solve 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

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 (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).
  • 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.
  • 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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