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🗂 We’re Hiring: LLM Engineer🕒 Employment Type: Full-Time💼 Level: Entry-Level to Mid-LevelWe are seeking a highly motivated, innovative, and technically skilled LLM Engineer to join our growing AI engineering team. …
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About the role
🗂 We’re Hiring: LLM Engineer🕒 Employment Type: Full-Time💼 Level: Entry-Level to Mid-LevelWe are seeking a highly motivated, innovative, and technically skilled LLM Engineer to join our growing AI engineering team. This role is ideal for individuals passionate about Large Language Models, Generative AI, Natural Language Processing, AI applications, and building reliable, scalable intelligent systems.🎯 Key Responsibilities• Design, develop, test, and deploy LLM-powered applications and services.• Integrate commercial and open-source Large Language Models into production systems.• Develop and optimize prompts, system instructions, structured outputs, and model workflows.• Build Retrieval-Augmented Generation (RAG) systems using embeddings, vector databases, and semantic search.• Develop LLM APIs and integrate AI capabilities into existing applications and business workflows.• Create evaluation frameworks to measure model accuracy, relevance, latency, reliability, and cost.• Prepare, process, and validate datasets for model evaluation, fine-tuning, and application development.• Support model fine-tuning, adaptation, and optimization for specialized use cases.• Integrate LLMs with databases, APIs, enterprise systems, and external tools.• Implement context management, memory, function calling, tool usage, and structured responses.• Monitor and optimize model performance, inference speed, scalability, and operational costs.• Implement guardrails, validation mechanisms, safety controls, and output quality checks.• Troubleshoot hallucinations, model failures, API issues, and production problems.• Collaborate with AI Engineers, Software Developers, Data Scientists, Product Managers, and DevOps teams.• Research emerging LLM architectures, AI frameworks, models, evaluation methods, and industry best practices.• Maintain technical documentation covering models, prompts, datasets, evaluations, APIs, and system architecture.✅ Requirements• Bachelor’s degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, Software Engineering, or a related field is preferred.• Experience with LLMs, Generative AI, NLP, machine learning, or software engineering is an advantage.• Strong programming skills in Python or another modern programming language.• Strong understanding of LLM concepts, Transformers, tokenization, embeddings, inference, and model evaluation.• Familiarity with LLM APIs and commercial or open-source model platforms is an advantage.• Experience with LangChain, LangGraph, LlamaIndex, Hugging Face, or similar AI frameworks is a plus.• Understanding of RAG architectures, vector databases, semantic search, and embeddings.• Familiarity with REST APIs, databases, Git, Docker, and cloud platforms.• Experience with PyTorch, TensorFlow, or other machine learning frameworks is an advantage.• Understanding of prompt engineering, fine-tuning, model evaluation, and AI application development.• Strong analytical, experimentation, debugging, and problem-solving skills.• Excellent attention to detail and ability to critically evaluate AI-generated outputs.• Strong communication and collaboration skills.• Good written and verbal communication skills in English.• Strong interest in Generative AI, LLMs, and emerging AI technologies.🌟 What We Offer• Hands-on experience developing real-world LLM and Generative AI applications.• Exposure to RAG, vector databases, prompt engineering, model evaluation, fine-tuning, and AI infrastructure.• Opportunities to work with modern commercial and open-source language models.• Structured training and mentorship from experienced AI and software engineering professionals.• Career progression into Senior LLM Engineer, AI Engineer, AI Research Engineer, AI Solutions Architect, or AI Technical Lead roles.• Opportunities to work on innovative AI products and intelligent automation projects.• Dynamic, innovative, and technology-driven working environment.• Continuous learning and professional development opportunities.• Competitive compensation with performance-based incentives.
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