Description : Were Hiring : AI Engineer - LLMs / GenAI / RAG

Location : Bangalore / Chennai

Experience : 1-4 Years

Type : Full-time (Work From Office Only)

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 fine-tuning methods (LoRA, PEFT, adapters) for domain-specific use cases.

- Integrate AI models with backend and frontend systems using APIs, batching, caching, and streaming responses.

- Deploy and optimize LLMs and embeddings via APIs and open-source frameworks (OpenAI, Anthropic, LLaMA-family, Mistral, etc.).

- Develop and maintain secure AI APIs using FastAPI/gRPC with Kubernetes and CI/CD pipelines.

- Implement AI safety and compliance measures such as prompt injection defenses, hallucination reduction, and PII redaction.

- Collaborate with MLOps and platform engineering teams to ensure scalable deployments using Docker, Kubernetes, and Ray/Serve.

- Utilize 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 (RAG) pipelines.

Mandatory Skills :

- Strong hands-on experience with LLMs, embeddings, and fine-tuning techniques.

- Proficiency in Python with experience using LangChain or Hugging Face.

- Experience with MLOps tools - Docker, Kubernetes, and CI/CD pipelines.

- Strong understanding of model integration and scalable API development.

- Familiarity with AI safety, security, and compliance mechanisms.

Desirable / Nice-to-Have :

- Exposure to speech-to-text models (e.g., Whisper), especially for Indian languages.

- Experience working in NBFC / BFSI domains.