GenAI professional

6 days ago


Bangalore, India Grid Dynamics Full time

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 Continuous Learning & Adaptability Quickly unlearn outdated practices and adapt to emerging GenAI and Agentic AI technologies .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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