Enterprise AI Experience Mgr

Key Skills

HTML, JavaScript, Analytical and Problem solving, Project management, CSS, Python Programming, Scrum Agile Methodology, Azure, AWS, Aartificial intelligence, Machine learning techniques, Data science techniques, Docker, Kubernetes-K8s, Continuous Integration & Continuous Delivery - CI/CD, Google Cloud Platform (GCP), Program Management, MLOps tools, Effective communication skills

Job Description

As an AI Experience Manager, you'll collaborate across teams to optimize the enterprise Model Development Lifecycle (MDLC) platform, ensuring a seamless journey for all AI solution types. Your role involves managing the enterprise AI platform for efficient submission, deployment, monitoring, and integration of AI use cases. This includes refining processes, enhancing communication channels, and ensuring efficient handling of each use case. You'll closely collaborate with AI developers, stakeholders, and end-users to create a user-friendly MDLC process aligned with Enterprise strategy and tailored to the needs of users.

Key Responsibilities and Duties

• Manage the Al Experience platform as the product owner, focusing on efficiency and maximizing its value.
• Develop strategies to optimize Al use case submission and management process addressing any inefficiencies.
• Ensure alignment of use cases with Enterprise strategy and AI standards and policies, coordinating with development teams for smooth integration.
• Establish efficient communication channels and protocols for submitting, tracking, and reviewing use cases.
• Implement mechanisms for automated use case feedback, notifications, and efficient model management.
• Partner with leadership to align roadmap priorities with broader enterprise and Al strategies and collaborate cross-functionally for continuous enhancement of the AI platform.
• Organize training sessions for users and development teams on use case submission and standard operating processes.
• Define metrics for evaluating the Al Experience journey and user feedback to enhance the overall experience.
• Drive the development of Al Experience framework features to enhance efficiency and business outcomes.
• Resolve exceptions and escalations related to use case and model journeys in collaboration with cross-functional teams.

Educational Requirements

• University (Degree) Preferred

Work Experience

• 5+ Years Required; 7+ Years Preferred

Physical Requirements

• Physical Requirements: Sedentary Work

Career Level

9IC

Minimum Requirements:

• At least 2 years of experience as product owner/manager for data Science or AI/ML
• At least 2 years of experience leading and supervising ML/AI solution projects in team settings

Preferred Qualifications:

• Experience in developing and deploying cloud-based solutions with

• a focus on AI/ML with proven track record of building robust and scalable ML pipelines and model production.

• Demonstrated experience with cloud platforms like AWS, Google Cloud, or Azure.

• Demonstrated work experience with MLOps practices and tools for seamless model development, deployment, and monitoring (CI/CD).

• Demonstrated knowledge of AI and/or Machine learning concepts, and frameworks.

• Familiarity with front-end and back-end technologies such as JavaScript, Python, HTML, CSS, and relevant frameworks.

• Familiarity with containerization technologies like Docker and orchestration tools like Kubernetes.

• Excellent communication and collaboration skills.

• Ability to work in an Agile/Scrum environment

Related Skills

Adaptability, Collaboration, Communication, Consultative Communication, Executive Presence, General Risk Management, Influence, Problem Solving, Program Management, Project Management, Relationship Management, Stakeholder Engagement

Anticipated Posting End Date:

2024-03-15

Base Pay Range: $122,600/yr. - $203,900/yr.

Actual base salary may vary based upon, but not limited to, relevant experience, time in role, base salary of internal peers, prior performance, business sector, and geographic location. In addition to base salary, the competitive compensation package may include, depending on the role, participation in an incentive program linked to performance (for example, annual discretionary incentive programs, non-annual sales incentive plans, or other non-annual incentive plans).