We are looking for a highly skilled and innovative Generative AI Engineer with hands-on experience in building, deploying, and scaling AI-driven applications. The ideal candidate should possess strong expertise in large language models (LLMs), retrieval-augmented generation (RAG), Python development, microservices architecture, and AI tool implementation. The role involves designing intelligent AI solutions, integrating advanced AI capabilities into enterprise applications, and optimizing AI systems for performance, scalability, and reliability.
Responsibilities
- Design, develop, and deploy generative AI applications using modern AI/ML frameworks and cloud platforms.
- Build and optimize applications leveraging Large Language Models (LLMs) such as GPT, Claude, Llama, Gemini, or similar models.
- Develop Retrieval-Augmented Generation (RAG) pipelines using vector databases and semantic search techniques.
- Implement AI agents, copilots, chatbots, and intelligent automation solutions.
- Design scalable microservices-based architectures for AI applications.
- Integrate AI solutions with enterprise systems, APIs, and third-party platforms.
- Fine-tune, evaluate, and optimize AI models for accuracy, latency, and cost efficiency.
- Develop and maintain REST APIs and backend services using Python frameworks.
- Work with embeddings, prompt engineering, model orchestration, and AI workflow automation.
- Deploy AI applications using Docker, Kubernetes, CI/CD pipelines, and cloud-native technologies.
- Collaborate with cross-functional teams including product, DevOps, data engineering, and business stakeholders.
- Ensure AI governance, security, scalability, and responsible AI practices.
- Stay updated with the latest advancements in AI, GenAI, and emerging technologies.
Requirements
- Strong proficiency in Python.
- Hands-on experience with LLMs (large language models).
- Experience in building RAG (Retrieval-Augmented Generation) systems.
- Strong understanding of data structures and algorithms.
- Experience with microservices architecture.
- Knowledge of REST APIs, API Gateway, and backend integration.
- Experience with AI tool implementation and deployment (preferred to have ATS or any recruitment tool experience).
- Familiarity with prompt engineering and AI model optimization.
- Understanding of vector databases such as Pinecone, Weaviate, ChromaDB, FAISS, or Milvus.
- Experience with LangChain, LlamaIndex, Semantic Kernel, or similar orchestration frameworks.
- Experience with AI agent frameworks and workflow automation.
This job was posted by Namrata Chauhan from Patch Infotech.
