Quick Overview
Job Description
Generative AI Engineer
Job Description
We are looking for a skilled Generative AI Engineer to design, develop, and deploy AI-powered applications using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and modern machine learning technologies. The ideal candidate should have hands-on experience building scalable AI solutions and integrating them into enterprise applications.
Key Responsibilities
Design and develop Generative AI applications using LLMs such as GPT, Claude, or Gemini.
Build and implement RAG pipelines using vector databases and embedding models.
Develop AI agents, prompt engineering workflows, and LLM-based solutions.
Work with frameworks such as LangChain, LangGraph, or LlamaIndex.
Integrate AI models with APIs, databases, and enterprise systems.
Optimize model performance, accuracy, latency, and cost.
Implement AI evaluation, monitoring, security, and responsible AI practices.
Collaborate with data scientists, software engineers, and business teams.
Required Skills
Strong programming experience in Python.
Hands-on experience with Generative AI, LLMs, and prompt engineering.
Experience with RAG, embeddings, and vector databases such as Pinecone, FAISS, or Chroma.
Knowledge of LangChain, LangGraph, or LlamaIndex.
Experience developing REST APIs using FastAPI or Flask.
Familiarity with cloud platforms such as AWS, Azure, or Google Cloud Platform.
Knowledge of machine learning, NLP, Git, and Docker.
Preferred Qualifications
Experience with AI agents and multi-agent systems.
Knowledge of model fine-tuning and LLM evaluation.
Experience with Kubernetes, CI/CD, and production AI deployments.
Strong problem-solving and communication skills.
How to Apply
Interested candidates can share their updated resume along with their current location, work authorization, expected rate, and availability.
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