AI Engineering Specialist

4 days ago

kurnool, India beBeeAgentic Full time

Unlock the Power of AI EngineeringAbout Us:We're a leader in simplifying enterprise private clouds, enabling IT teams to manage VMs and containers with ease.Our flagship product turns existing infrastructure into a full-featured private cloud, meeting all enterprise requirements for familiar VM management experience, critical virtualization features, and compatibility with all hardware environments.With over 30,000 nodes in production at top enterprises, we've established ourselves as a driving force in private cloud innovation.Key Responsibilities:Develop Intelligent AI Solutions: Leverage state-of-the-art AI technologies to build pioneering NLP and Generative AI solutions that solve real-world infrastructure problems.Own Key AI Features: Drive the end-to-end development of LLM-powered applications, chatbots, and optimization engines that improve operational efficiency and resilience.Build and Deploy Agentic AI Platforms: Develop AI-powered observability and autoscaling frameworks for large-scale distributed systems.Integrate AI/ML Solutions: Integrate AI/ML solutions into CI/CD pipelines, monitoring, and platform APIs.Collaborate with Cross-Functional Engineers: Deliver high-impact operational experiences through collaboration and expertise sharing.Qualifications and Skills:Minimum bachelor's degree in Data Science or related field.5+ years of experience, with at least 2 years working on generative AI technologies.Solid understanding of transformers and modern NLP / LLM techniques; experience with fine-tuning or prompting large language models.Strong proficiency in Python, with exposure to Golang a plus.Working knowledge of deployment using Kubernetes on Cloud infrastructure desirable.Proven ability to build scalable, reliable production services.Distinguish Yourself:Agentic AI Mastery: Practical experience with frameworks like LangChain or LangGraph, and a deep understanding of multi-step reasoning and planning.LLM Inference Optimization: Expertise in accelerating LLM inference to achieve low latency at scale.End-to-End ML Systems Ownership: A portfolio showing full lifecycle ownership from data ingestion to monitoring and continuous improvement.

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