Large Language Model Architect

1 day ago

Jaipur, Rajasthan, India beBeeai Full time ₹ 80,00,000 - ₹ 1,50,00,000

Job Title: AI Solution Architect

We are seeking a highly skilled Ai solution architect to join our team. As an AI solution architect, you will be responsible for designing and implementing large language models into enterprise applications.

  • AI Model Development: Develop, fine-tune, and integrate LLMs (GPT, LLaMA, Claude, etc.) into enterprise applications.
  • Prompt Engineering and RAG Pipelines: Implement prompt engineering techniques, embeddings, and RAG (Retrieval Augmented Generation) pipelines.
  • Agentic AI Applications: Build and maintain Agentic AI applications using Langgraph, etc.
  • API Design and Microservices: Design and maintain APIs, microservices, and front-end/back-end integrations for GenAI applications.
  • Vector Databases and Semantic Search: Work with vector databases (Pinecone, FAISS, Weaviate, Milvus) to enable semantic search.
  • Cloud Deployment: Deploy solutions on cloud AI platforms (Azure OpenAI, AWS Bedrock, GCP Vertex AI).
  • Model Optimization: Optimize model performance, latency, and scalability for real-world usage.
  • Collaboration and Security: Collaborate with data scientists and solution architects to deliver PoCs and production-ready applications, ensuring AI solutions follow responsible AI, data privacy, and security guidelines.

Responsibilities:

  1. Fine-Tuning and Integration: Develop, fine-tune, and integrate LLMs (GPT, LLaMA, Claude, etc.) into enterprise applications.
  2. Prompt Engineering and RAG Pipelines: Implement prompt engineering techniques, embeddings, and RAG (Retrieval Augmented Generation) pipelines.
  3. Agentic AI Applications: Build and maintain Agentic AI applications using Langgraph, etc.
  4. API Design and Microservices: Design and maintain APIs, microservices, and front-end/back-end integrations for GenAI applications.
  5. Vector Databases and Semantic Search: Work with vector databases (Pinecone, FAISS, Weaviate, Milvus) to enable semantic search.
  6. Cloud Deployment: Deploy solutions on cloud AI platforms (Azure OpenAI, AWS Bedrock, GCP Vertex AI).
  7. Model Optimization: Optimize model performance, latency, and scalability for real-world usage.
  8. Collaboration and Security: Collaborate with data scientists and solution architects to deliver PoCs and production-ready applications, ensuring AI solutions follow responsible AI, data privacy, and security guidelines.

Requirements:

  • Technical Skills: Experience in developing, fine-tuning, and integrating large language models into enterprise applications.
  • Programming Languages: Proficient in programming languages such as Python, Java, or C++.
  • Data Science Tools: Familiarity with data science tools such as TensorFlow, PyTorch, or Keras.
  • Cloud Platforms: Experience with cloud platforms such as Azure OpenAI, AWS Bedrock, or GCP Vertex AI.

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