Overview

We are looking to connect with a Chief Intelligence Officer with the following skill and expertise:-

  • AI Roadmap vis-a-vis Business vision/goals/initiatives (VGIs)
  • Ideas & insights into newer AI-powered business models
  • Projects/products implementation methodologies/processes (agile etc.)
  • AI algorithms, research & related roadmap
  • Technologies & related roadmap
  • AI platform/products architecture/design/implementation vis-a-vis cloud AI services
  • AI governance (ethical AI) and related processes
  • AI infrastructure vis-a-vis cloud AI services
  • AI automation (pipeline) projects
  • AI/ML models quality assurance strategy
  • AI/ML models continuous delivery/deployment strategies

The following represents details related to some of the above:

 

  1. Identify AI projects of high business impact including both product-related projects, and also research projects. Collaborate/communicate effectively with product owners representing different product lines.
  2. Prepare an annual roadmap for implementation of different AI projects.
  3. Provide ideas and insights into new business models that could be enabled using AI. Become a go-to-guy for C-Suite executives for implementing AI in their functional areas.
  4. Layout the AI projects/products implementation processes (ML model development lifecycle) including project inception, exploration phase, model building phase, model deployment, and model retraining. Ensure the project implementation governance on the ongoing basis.
  5. Prepare the plan and oversee the implementation of the AI platform which will be used to deploy and host ML models.
  6. Play a key role in deciding technologies and related roadmap for development, testing, deployment of AI/machine learning models.
  7. Prepare the plan and oversee the implementation of quality assurance processes in relation to model testing by different stakeholders; Model performance testing, model acceptance testing by product managers/consultants/customers, other forms of testing as applicable (such as metamorphic testing, dual coding testing, blackbox, white-box testing etc)
  8. Prepare the plan and oversee the implementation of continuous delivery/deployment strategies (A/B testing, canary testing etc) of machine learning models.
  9. Prepare the strategy/plan for ethical AI and oversee its implementation across different AI projects. Get involved with the interaction related to ethical AI with stakeholders including customers/partners AI governance team, auditors, regulators on the ongoing basis.
  10. Prepare the plan and oversee the implementation of machine learning pipeline automation to be used for automated ML model retraining/testing across different AI projects.
  11. Prepare the plan and oversee the implementation of AI infrastructure to be used for model training/retraining and model deployment in production. Ensures the use of cloud services vis-a-vis local infrastructure for fulfilling different requirements.
  12. Hire a team of data scientists; Keep a check on newer hiring requirements on the ongoing basis. Provide training and mentoring to the team.