Chief Artificial Intelligence Architect

1 day ago


Kota, Rajasthan, India beBeeArtificial Full time ₹ 1,50,00,000 - ₹ 2,50,00,000
Job Title: Chief Artificial Intelligence Architect

We are seeking a seasoned Chief Artificial Intelligence Architect to lead the development of our Large Language Model (LLM). As a key member of our team, you will be responsible for designing and overseeing the architecture of our LLM, ensuring it aligns with our business objectives.

  • Design & Oversee AI Architecture: Develop the overall architecture for the Large Language Model (LLM), focusing on scalability, modularity, and security principles.
  • Technical Strategy & Roadmap: Define the technical strategy and create a roadmap in line with organizational goals, including integration of data pipelines, model training environments, and deployment infrastructure.
  • Technology Selection: Decide on the technology stack, frameworks, and tools for LLM development and deployment, considering big data technologies, data pipeline design, and data management practices.
  • Integration Management: Oversee the integration of different components, ensuring seamless interaction between them.
  • Risk Management: Identify potential technical risks and define mitigation strategies to ensure the success of the project.
  • Collaboration: Work closely with data scientists, engineers, domain experts, and stakeholders to achieve cohesive implementation.
  • Innovation & Best Practices: Stay updated with AI advancements and incorporate best practices to improve LLM capabilities, conducting in-depth research on LLM architectures.

Required Skills & Qualifications:

  • Ai/Ml Expertise: Deep knowledge in AI, ML, NLP, and large language models (LLMs).
  • Software Architecture: Strong grasp of scalability, modularity, and security principles.
  • Cloud Proficiency: Hands-on experience with AWS, Azure, or Google Cloud.
  • Data Architecture: Knowledge of big data technologies, data pipeline design, and data management practices.
  • Mlops: Expertise in CI/CD, deployment, and monitoring for ML models.
  • Leadership: Ability to guide technical teams and communicate effectively with stakeholders.
  • Problem-Solving: Strong analytical skills for addressing complex technical challenges.


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