Description

You will design, develop, and deploy Generative AI (GenAI) applications using large language models (LLMs) and Python.

Responsibilities

• Build and maintain production-grade Python APIs, microservices, and data pipelines for GenAI integration.
• Fine-tune and optimize pre-trained LLMs (OpenAI, Hugging Face, Anthropic, Llama) for domain-specific use cases.
• Implement prompt engineering strategies and leverage vector databases (Pinecone, Weaviate, FAISS, Milvus) for RAG solutions.
• Integrate GenAI technologies with cloud AI services (AWS Sagemaker, Azure OpenAI, GCP Vertex AI).
• Apply MLOps best practices, including model lifecycle management using CI/CD, Docker, Kubernetes, MLflow, and Kubeflow.

Required Skills

• 5+ years of professional experience.
• Expertise in Python development.
• Experience integrating with AWS SageMaker, Azure OpenAI, and GCP Vertex AI.
• Proficiency with PyTorch.
• Experience building and maintaining production APIs and data pipelines.
• Knowledge of LLM fine-tuning and prompt engineering.
• Familiarity with vector databases (Pinecone, Weaviate, FAISS, Milvus).
• Experience applying MLOps principles (CI/CD, Docker, Kubernetes, MLflow).
• Experience in financial or banking domains is preferred.

Key Skills

Education

Any Graduate