Chief Data Architect for Generative AI

2 days ago

Chennai, Tamil Nadu, India beBeeDataArchitecture Full time ₹ 15,00,000 - ₹ 25,00,000
Job Description:

We are seeking a highly skilled Chief Data Architect for Generative AI to design and implement robust data architectures that support AI and machine learning (ML) workloads, including Generative AI applications.

This role will involve developing and optimizing data pipelines for training, validating, and deploying AI models efficiently and securely. The successful candidate will also integrate AI frameworks into data platforms, ensuring scalability, low latency, and high throughput.

In addition, the Chief Data Architect for Generative AI will collaborate with data scientists, AI engineers, and stakeholders to align data strategies with business goals. This includes leading initiatives to ensure data governance, security, and compliance standards (e.g., GDPR, CCPA) are met in AI-driven environments.

Required Skills and Qualifications:
  • Data Architecture: 5+ years of experience in designing and implementing data architectures for AI/ML-enabled systems.
  • Generative AI: Hands-on experience with Generative AI models (e.g., OpenAI GPT, BERT, or similar), including fine-tuning and deployment.
  • Data Engineering: Proficiency in data engineering tools and frameworks (e.g., Apache Spark, Hadoop, Kafka).
  • Database Systems: Deep knowledge of database systems (SQL, NoSQL) and cloud platforms (AWS, Azure, GCP), including their AI/ML services (e.g., AWS Sagemaker, Azure ML, GCP Vertex AI).
  • MLOps: Strong understanding of data governance, MLOps, and AI model lifecycle management.
Benefits:
  • Experience Integration: Experience integrating generative AI solutions into production-level applications.
  • Knowledge Base: Knowledge of vector databases (e.g.,
  • APIs for AI Models: Expertise in APIs for AI models (e.g., OpenAI API or Hugging Face Transformers).
Others:
  • Educational Background: A bachelor's degree in Computer Science, Data Engineering, or a related field (master's preferred).
  • Language Skills: Proficiency in programming languages such as Python or R and frameworks like TensorFlow or PyTorch.
  • Prompt Engineering: Familiarity with LLM fine-tuning, prompt engineering, and embedding models.

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