Job Summary :

We are seeking a talented Generative AI Engineer to design, develop, and deploy AI-powered solutions using Large Language Models (LLMs) and other Generative AI technologies. The ideal candidate will have experience in machine learning, prompt engineering, model fine-tuning, and AI application development.

Key Responsibilities :

- Design, develop, and implement Generative AI solutions using LLMs.

- Build AI-powered applications such as chatbots, virtual assistants, and content-generation tools.

- Develop and optimize prompts for improved model performance.

- Fine-tune and evaluate foundation models based on business requirements.

- Integrate AI models with APIs, databases, and enterprise applications.

- Collaborate with cross-functional teams to understand business needs and translate them into AI solutions.

- Monitor model performance, accuracy, and scalability.

- Ensure compliance with AI governance, security, and ethical standards.

- Stay updated with the latest advancements in Generative AI and machine learning.

Required Skills :

- Strong knowledge of Generative AI, LLMs, NLP, and Machine Learning.

- Experience with OpenAI, Gemini, Claude, Llama, or similar AI models.

- Proficiency in Python and AI frameworks such as LangChain, Hugging Face, TensorFlow, or PyTorch.

- Experience with vector databases and Retrieval-Augmented Generation (RAG).

- Knowledge of prompt engineering and model evaluation techniques.

- Familiarity with cloud platforms such as AWS, Azure, or GCP.

- Understanding of REST APIs, microservices, and software development best practices.

Preferred Qualifications :

- Bachelor's or Master's degree in Computer Science, AI, Data Science, or a related field.

- 2-5+ years of experience in AI/ML development.

- Experience with fine-tuning, embeddings, and AI deployment pipelines.

- Knowledge of MLOps and AI governance frameworks.

Tools & Technologies :

- Python, SQL

- LangChain, LlamaIndex

- Hugging Face, TensorFlow, PyTorch

- OpenAI API, Gemini API, Claude API

- Vector Databases (Pinecone, FAISS, ChromaDB)

- AWS, Azure, GCP

- Git, Docker, Kubernetes