Interesting Job Opportunity: LTM - Generative AI/Agentic AI Engineer

Job description

**Job Description** **Key Responsibilities :** - Design, develop, and deploy Generative AI and Agentic AI solutions for enterprise use cases. - Build and optimize Retrieval-Augmented Generation (RAG) pipelines using vector databases and knowledge retrieval systems. - Develop intelligent AI agents and multi-agent systems using frameworks such as LangChain, LangGraph, CrewAI, LlamaIndex, NeMo Agent Toolkit (NAT), and related technologies. - Implement and fine-tune Large Language Models (LLMs) and multimodal AI models for various business applications. - Create effective prompts, prompt chains, and prompt optimization strategies to improve model performance and reliability. - Develop end-to-end AI/ML solutions involving NLP, deep learning, predictive analytics, and automation workflows. - Build scalable APIs and AI services for model inference and integration with enterprise applications. - Perform model evaluation, testing, monitoring, and optimization to ensure high accuracy and efficiency. - Collaborate with cross-functional teams including Data Scientists, Product Managers, Architects, and DevOps teams to deliver AI-driven solutions. - Deploy AI workloads on cloud environments and implement MLOps best practices. - Stay updated with emerging trends in Generative AI, Agentic AI, LLMs, and AI infrastructure technologies. **Required Technical Skills** **Generative AI & Agentic AI :** - Strong experience in Generative AI application development. - Hands-on experience with : - Retrieval-Augmented Generation (RAG) - Prompt Engineering - AI Agents and Multi-Agent Systems - Knowledge Retrieval Systems - Conversational AI Applications **AI/ML & Deep Learning** - Strong understanding of : - Machine Learning - Deep Learning - Natural Language Processing (NLP) - Large Language Models (LLMs) - Multimodal AI Models - Experience with : - Transformers - CNN (Convolutional Neural Networks) - RNN (Recurrent Neural Networks) - Fine-tuning and Model Optimization Techniques **LLMs & Foundation Models** - Hands-on experience with one or more of the following : - GPT Models - LLaMA - Mistral - Qwen - Nemotron - Other Open-Source Foundation Models **GenAI Frameworks** - Experience with : - LangChain - LlamaIndex - LangGraph - CrewAI - NeMo Agent Toolkit (NAT) - NVIDIA NeMo Framework **Programming & Data Science** - Strong proficiency in Python programming. - Experience with : - Pandas - NumPy - TensorFlow - Keras - PyTorch - Knowledge of software design principles and coding best practices. **Cloud & DevOps** - Hands-on experience with one or more cloud platforms : - Microsoft Azure - Amazon Web Services (AWS) - Google Cloud Platform (GCP) - Experience with: - Docker - Kubernetes - Git/GitHub/GitLab - CI/CD Pipelines - MLOps Concepts **Operating Systems** - Experience working in Linux and Windows environments. **Desired Qualifications** - Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, Engineering, or a related field. - Relevant certifications in AI/ML, Cloud Technologies, or Generative AI are preferred. - Experience working on enterprise-scale AI applications is highly desirable (ref:hirist.tech)