Artificial Intelligence Engineer

Description :

Key Responsibilities :

• Design and implement end-to-end data pipelines for training and fine-tuning LLMs, including dataset creation, cleaning, augmentation, and labeling workflows.
• Apply advanced RAG techniques, prompt engineering, and model fine-tuning (LoRA, PEFT, adapters) for domain-specific use cases.
• Integrate AI models with backend and frontend systems via APIs, batching, caching, and streaming responses.
• Deploy and optimize LLMs & embeddings using APIs and / or open-source models (OpenAI, Anthropic, LLaMA-family, Mistral, etc.).
• Develop and maintain secure AI APIs using FastAPI / gRPC with Kubernetes and CI / CD pipelines.
• Implement safety and compliance layers including prompt injection defenses, hallucination reduction, and PII redaction.
• Collaborate with MLOps and platform engineering teams to ensure scalable deployment using Docker, Kubernetes, and Ray / Serve.
• Leverage frameworks such as LangChain, Hugging Face Transformers, and Azure OpenAI for model orchestration and integration.
• Work with vector databases (FAISS, Pinecone, Milvus) to build efficient retrieval-augmented generation pipelines.

Mandatory Skills :

Desirable / Plus :

(ref : hirist.tech)