Job Title: LLM Engineer (Large Language Model Engineer)
Job Summary: We are seeking a highly skilled LLM Engineer to design, develop, fine-tune, and deploy Large Language Model (LLM) based applications and AI-powered solutions. The ideal candidate will have expertise in Generative AI, Natural Language Processing (NLP), Prompt Engineering, Retrieval-Augmented Generation (RAG), and AI system architecture. This role involves building intelligent assistants, AI copilots, enterprise search platforms, and automation solutions using cutting-edge LLM technologies.
Key Responsibilities: - Design, develop, and deploy applications powered by Large Language Models (LLMs).
- Build AI assistants, chatbots, knowledge management systems, and AI copilots.
- Develop and optimize Prompt Engineering strategies to improve model responses.
- Implement Retrieval-Augmented Generation (RAG) pipelines using vector databases.
- Fine-tune open-source and proprietary LLMs for domain-specific use cases.
- Integrate AI models with enterprise systems, APIs, databases, and cloud services.
- Develop evaluation frameworks to measure model performance, accuracy, and reliability.
- Implement guardrails, safety mechanisms, and hallucination mitigation techniques.
- Collaborate with Data Scientists, AI Engineers, Product Managers, and MLOps teams.
- Monitor, optimize, and maintain AI systems in production environments.
- Research and evaluate emerging AI models, frameworks, and architectures.
- Ensure compliance with Responsible AI, security, and governance standards.
Required Skills: - Strong understanding of Large Language Models (LLMs) and Generative AI concepts.
- Experience with NLP, Transformer architectures, and AI model deployment.
- Expertise in Prompt Engineering and Retrieval-Augmented Generation (RAG).
- Knowledge of AI evaluation, model optimization, and inference strategies.
- Strong problem-solving and system design skills.
- Excellent communication and collaboration abilities.
Technical Skills: - Programming Languages: Python, SQL, JavaScript
- LLM Platforms: OpenAI GPT, Claude, Gemini, Llama, Mistral, Cohere
- AI Frameworks: LangChain, LlamaIndex, LangGraph, Haystack
- Machine Learning Frameworks: PyTorch, TensorFlow, Hugging Face Transformers
- Vector Databases: Pinecone, ChromaDB, Weaviate, Milvus, FAISS
- Cloud Platforms: AWS, Azure, Google Cloud Platform (GCP)
- APIs: REST APIs, GraphQL
- MLOps Tools: MLflow, Kubeflow, Airflow
- Containerization: Docker, Kubernetes
- Version Control: Git, GitHub, GitLab
Qualifications: - Bachelor's degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a related field.
- Master's degree in AI, Data Science, or Machine Learning is a plus.
- Relevant AI and cloud certifications are preferred.
Experience: - 3-8 years of experience in AI Engineering, Machine Learning Engineering, NLP, or Software Development.
- Hands-on experience building and deploying LLM-powered applications.
- Experience with RAG architectures, vector databases, and AI orchestration frameworks.
- Experience integrating AI services into enterprise applications.
Preferred Qualifications: - Experience with fine-tuning techniques such as LoRA, PEFT, RLHF, and QLoRA.
- Knowledge of Agentic AI, Multi-Agent Systems, and Autonomous AI Workflows.
- Experience with LangGraph, CrewAI, AutoGen, or Semantic Kernel.
- Understanding of AI Security, Responsible AI, and Model Governance.
- Experience deploying AI applications in cloud-native environments.
Preferred Qualities: - Strong innovation and research mindset.
- Passion for AI, NLP, and emerging technologies.
- Excellent troubleshooting and analytical skills.
- Ability to rapidly learn and adapt to new AI frameworks.
- Strong ownership and accountability for AI solution quality.
Employment Type: Full-Time
Location: Remote / Hybrid / On-site
Nice to Have: - Experience building AI copilots, enterprise search systems, and knowledge assistants.
- Knowledge of multimodal AI models (text, image, audio, video).
- Experience with AI observability and evaluation platforms such as LangSmith, Arize AI, or Weights & Biases.
- Familiarity with enterprise SaaS, HR Tech, Healthcare, FinTech, E-commerce, or Customer Support AI solutions.
- Contributions to open-source AI projects, research papers, AI communities, or hackathons.
