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Urgent! Vitric Business Solutions - Artificial Intelligence Engineer - Python Job Opening In Pune – Now Hiring VITRIC BUSINESS SOLUTIONS PRIVATE LIMITED

Vitric Business Solutions Artificial Intelligence Engineer Python



Job description

<p><p><b>Description : </b></p><br/><p><br/></p><p>AI Engineer.</p><br/><br/><p>We are seeking an experienced AI Engineer with expertise in Python and prompt engineering.</p><br/><br/><p>The ideal candidate will have a minimum of 2+ years of relevant experience, a good understanding of LLMs, LangGraph, LangChain, and AutoGen is a professional who designs, develops, and deploys intelligent systems utilizing large language models (LLMs) and advanced AI frameworks.</p><br/><br/><p><b>Python Proficiency : </b></p><br/><p><br/></p><p>- Strong programming skills in Python are fundamental for developing and implementing AI solutions.</p><br/><br/><p><b>Prompt Engineering : </b></p><br/><p><br/></p><p>- Expertise in crafting effective prompts to guide LLMs towards generating desired and accurate responses, often involving techniques like prompt chaining and optimization.</p><br/><br/><p><b>LLM Application Development : </b></p><br/><p><br/></p><p>- Hands-on experience in building applications powered by various LLMs (e.g., GPT, LLaMA, Mistral).</p><br/><br/><p>- This includes understanding LLM architecture, memory management, and function/tool calling.</p><br/><br/><p><b>Agentic AI Frameworks : </b></p><br/><p><br/></p><p>Proficiency with frameworks designed for building AI agents and multi-agent systems, such as : </p><br/><br/><p>- LangChain : A framework for developing applications powered by language models, enabling chaining of components and integration with various tools and data sources.</p><br/><br/><p>- LangGraph : An extension of LangChain specifically designed for building stateful, multi-actor applications using LLMs, often visualized as a graph of interconnected nodes representing agents or logical steps.</p><br/><br/><p>- AutoGen : A Microsoft framework that facilitates multi-agent collaboration, allowing specialized agents to work together to solve complex problems through task decomposition and recursive feedback Generation (RAG) : </b></p><br/><p><br/></p><p>- Experience in implementing and optimizing RAG pipelines, which combine LLMs with external knowledge bases (e.g., vector databases) to enhance generation with retrieved and MLOps : </b></p><br/><p><br/></p><p>- Practical knowledge of deploying AI models and agents into production environments, including containerization (Docker), orchestration (Kubernetes), cloud platforms (AWS, Azure, GCP), and CI/CD pipelines.</p><br/></p> (ref:hirist.tech)


Required Skill Profession

Computer Occupations



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