We are looking for a highly skilled AI Developer with expertise in Large Language Models (LLMs) to design, develop, and deploy intelligent AI-driven solutions tailored to client requirements. The ideal candidate will have a strong understanding of NLP, RAG (Retrieval-Augmented Generation), vector databases, and prompt engineering. You will collaborate closely with clients, business analysts, and technical teams to translate business problems into scalable AI solutions.
Key Responsibilities
- Collaborate with clients to analyze requirements and identify AI-driven opportunities and use cases.
- Design and develop custom AI/GenAI solutions using OpenAI, Anthropic, or similar LLM APIs.
- Implement Retrieval-Augmented Generation (RAG) pipelines integrating embeddings, vector stores, and knowledge bases.
- Fine-tune and optimize LLMs for domain-specific applications.
- Build and deploy chatbots, knowledge assistants, and automation tools using frameworks like LangChain, LlamaIndex, or custom architectures.
- Integrate AI solutions with enterprise applications, APIs, and data sources (structured and unstructured).
- Work with vector databases (e.g., Chroma, Pinecone, FAISS, Weaviate) for semantic search and retrieval.
- Perform prompt engineering and optimization for improved LLM responses and accuracy.
- Evaluate, test, and benchmark different AI models, embeddings, and APIs for specific use cases.
- Stay updated with advancements in AI, ML, and GenAI technologies to propose innovative solutions for clients.
Required Skills & Experience
- 4–6 years of experience in AI/ML development, with at least 1–2 years in LLM-based projects.
- Hands-on experience with OpenAI GPT models, LangChain, LlamaIndex, or similar frameworks.
- Strong knowledge of Python, FastAPI/Flask, and RESTful API development.
- Experience with vector databases (Chroma, Pinecone, FAISS, etc.) and embedding models (e.g., ada-002).
- Solid understanding of NLP, machine learning, and RAG architectures.
- Familiarity with prompt design, fine-tuning, and model evaluation techniques.
- Exposure to Streamlit, Gradio, or similar front-end tools for AI demos.
- Working knowledge of cloud platforms (Azure, AWS, or GCP) and deployment pipelines.
- Strong analytical and problem-solving skills with the ability to translate business needs into technical solutions.
- Excellent communication and client interaction skills.
Nice to Have
- Experience with multimodal AI (text, image, or document processing).
- Familiarity with open-source LLMs (Llama 3, Mistral, Falcon, etc.).
- Knowledge of AI ethics, governance, and data privacy considerations.
Education
- Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, or related field.