Job Description :

Job Responsibilities

  • Participate in analyzing the current technology selection process (TSP) workflows and identifying areas for enhancement to meet AI remediation requirements for acquiring new products and services with models.
  • Participate in developing and maintaining AI controls within the architecture profile and/or template, ensuring that the overall design solution undergoes P/EARB review whenever there are one or more models involved, and validating the AI/ML requirements during the architecture review board (ARB).
  • Regularly update and refine the AI controls, incorporating them into the architecture profile and template to ensure compliance and alignment with evolving needs and requirements.
  • Collaborate with stakeholders to analyze the current and target states of the Approved Software List (ASL), Business Assets Registry (BAR), and Model Usage Inventory Management (MUSE) data synchronization.
  • Identify areas for enhancement in order to meet AI remediation requirements and ensure effective synchronization between the ASL, BAR, and MUSE systems.
  • Work with the enterprise architecture policies and standards team to incorporate AI-related requirements specified and needed during the technology selection and architecture review processes.
  • Document and socialize the revised TSP workflows, incorporating models, and provide training to stakeholders on their utilization.
  • Collaborate with adaptive digital architecture governance (ADAG) stakeholders, including the process, architecture, and model review teams, to gather input and feedback on the controls required to revise the architecture profile and/or template during the architecture review process.
  • Collaborate with stakeholders to define and implement the necessary data synchronization requirements to synchronize data between the ASL, BAR, and MUSE systems.
  • Participate in developing and maintaining the plan for the listed workstreams.

Skills

  • Strong understanding of the Software Development Life Cycle (SDLC).
  • Proficiency in requirement gathering and documentation.
  • Expertise in enterprise architecture, with a focus on AI models and controls.
  • Knowledge and experience in model-based development and reviewing, specifically related to AI models.
  • Understanding of data synchronization principles and techniques.
  • Adaptability and flexibility to evolving needs and requirements.
  • Strong collaboration and communication skills.
  • Optional: Familiarity with ServiceNow.
             

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