GenAI Engineer

What you'll work on

• Develop, fine-tune, and optimize Large Language Models (LLMs) and other generative models (text, image, audio, and multimodal).
• Build production-grade GenAI applications , including chatbots, copilots, automation tools, and content-generation systems.
• Integrate LLMs with backend systems, APIs, databases, and enterprise platforms.
• Implement retrieval-augmented generation (RAG) pipelines using vector databases and embedding models.
• Evaluate model performance, run experiments, and improve accuracy, relevance, and latency.
• Create prompts, prompt frameworks, and prompt-engineering guidelines for different use cases.
• Develop model safety, guardrails, and security controls to ensure responsible use of AI.
• Collaborate with data engineers, software developers, and product stakeholders to deliver scalable AI solutions.
• Maintain documentation, best practices, and technical guidance for AI platforms.

Required Skills & Qualifications

• Strong experience with LLMs , generative AI frameworks, and transformer-based architectures.
• Hands-on knowledge of tools such as:
• OpenAI API , Azure OpenAI, Anthropic, Hugging Face, LangChain, LlamaIndex, Vertex AI, or similar.
• Proficiency in Python and ML/AI libraries (PyTorch, TensorFlow, Transformers).
• Experience building RAG pipelines , vector databases (Pinecone, FAISS, Weaviate, Chroma), and embeddings.
• Understanding of machine learning workflows, including fine-tuning, evaluation, and deployment.
• Ability to work with unstructured data (text, documents, images, audio).
• Familiarity with cloud platforms (AWS, Azure, GCP) and containerization (Docker, Kubernetes).
• Strong problem-solving, experimentation, and communication skills.