Chief AI Integration Specialist

3 days ago

Tiruppur, Tamil Nadu, India beBeeArtificial Full time ₹ 1,50,00,000 - ₹ 2,50,00,000
Generative AI Engineer

We are seeking a skilled Generative AI Engineer to join our team.

  • Job Description:
  • Develop and Integrate LLMs: Fine-tune and integrate large language models (LLMs) like GPT, LLaMA, Claude into enterprise applications.
  • Prompt Engineering and RAG Pipelines: Implement prompt engineering techniques, embeddings, and Retrieval Augmented Generation (RAG) pipelines to enhance model performance.
  • Agentic AI Applications: Understand building agentic AI applications using Langgraph and other frameworks.
  • APIs and Integrations: Build 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 functionality.
  • Cloud AI Deployments: Deploy solutions on cloud AI platforms (Azure OpenAI, AWS Bedrock, GCP Vertex AI) and optimize model performance, latency, and scalability.
  • Collaboration and Responsible AI: Collaborate with data scientists and solution architects to deliver proof-of-concepts (PoCs) and production-ready applications while ensuring responsible AI, data privacy, and security guidelines are followed.
  • Required Skills and Qualifications:
  • Programming Skills in Python: Strong programming skills in Python (preferred) with experience in APIs, microservices, Flask/FastAPI/Django.
  • Azure Databricks and Apache Spark: Hands-on experience with Azure Databricks and Apache Spark for big data processing.
  • Vector Embeddings and Vector Databases: Knowledge of vector embeddings and vector databases for efficient storage and retrieval.
  • Orchestration Frameworks: Experience with LangChain, LlamaIndex, or similar orchestration frameworks for managing complex workflows.
  • Docker, Kubernetes, and MLOps: Familiarity with Docker, Kubernetes, and MLOps practices for deploying AI models and managing infrastructure.
  • Cloud-Based AI Services: Experience working with cloud-based AI services (Azure, AWS, or GCP) and strong problem-solving and debugging skills.
  • PyTorch, TensorFlow, and Transformers: Good to have experience with PyTorch, TensorFlow, and Hugging Face Transformers for deep learning tasks.

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