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AI Architect – Generative AI

AI Architect – Generative AI

MindBrainMumbai, IN
2 days ago
Job description

Job Title : AI Architect – Generative AI

Experience : 8–10 Years

Location : Remote (Contractual Role)

Duration : 12 months

Type : Contract (Full-time / Part-time – depending on your need)

Job Summary :

We are seeking a highly experienced AI Architect with a strong background in AI / ML systems architecture and Generative AI technologies to lead the design and implementation of innovative, AI-driven solutions. The ideal candidate will be responsible for driving end-to-end AI architecture, with a strong focus on LLMs, transformer models, embeddings, RAG pipelines , and deploying enterprise-ready AI applications at scale.

Key Responsibilities :

  • Design, develop, and oversee scalable AI / ML architectures across cloud and hybrid environments.
  • Lead the implementation of Generative AI solutions , including LLM-based applications (e.g., GPT, LLaMA, Claude).
  • Architect and optimize Retrieval-Augmented Generation (RAG) pipelines and vector database integration.
  • Collaborate with product, data science, and engineering teams to translate business requirements into robust AI systems.
  • Evaluate and integrate open-source and commercial GenAI models (e.g., Hugging Face, OpenAI, Anthropic).
  • Establish best practices for model fine-tuning , prompt engineering , and AI safety / compliance .
  • Drive PoC to production lifecycle for GenAI tools like chatbots, document summarizers, copilots, etc.
  • Maintain technical documentation, governance frameworks, and model performance monitoring.

Must-Have Skills :

  • 8–10 years of experience in AI / ML development and architecture .
  • Hands-on experience with Generative AI models like GPT, BERT, LLaMA, Claude, etc.
  • Deep knowledge of LLMs , transformer architectures , embedding models , and fine-tuning techniques .
  • Expertise in Python , TensorFlow / PyTorch , and Hugging Face Transformers .
  • Experience with LangChain , LLM orchestration , and vector DBs like Pinecone , FAISS , or Weaviate .
  • Solid understanding of cloud services (AWS / GCP / Azure), Kubernetes, and scalable model deployment strategies.
  • Familiarity with MLOps practices , including CI / CD for ML, experiment tracking, and monitoring.
  • Strong knowledge of data privacy , AI ethics , and responsible AI frameworks .
  • Preferred Skills :

  • Exposure to multi-modal models (vision + language).
  • Experience deploying enterprise GenAI use cases (e.g., document processing, customer support bots, knowledge assistants).
  • Contributions to open-source GenAI frameworks or communities.
  • Strong communication and stakeholder management skills.
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