Overview We are seeking an experienced AI Sustain lead focused on the ongoing management, optimization, and ethical compliance of AI systems throughout their lifecycle. The role emphasizes long-term maintenance to ensure AI applications remain effective, efficient, and aligned with organizational goals, especially as these systems integrate deeper into operations and user-facing products. This position also involves mentoring team members and driving best practices in AI systems and delivery across multiple platforms. Responsibilities Proficiency in generative AI model lifecycle, including training, deployment, and retraining processes Familiarity with platforms like TensorFlow Extended (TFX), Azure ML, Google Vertex AI, or other tools that automate model deployment and monitoring. Ability to engage with diverse teams, ensuring alignment on application goals, compliance standards, and performance expectations. Lead the architecture approval process, working with relevant stakeholders to ensure designs meet organizational standards and best practices across AI programs. Gather and analyze requirements from various teams, translating them into actionable cloud delivery plans. Conduct regular audits to identify potential biases and harmful content in the generated outputs, adjusting data inputs, prompts, or model configurations to mitigate these issues. Establish guidelines for ethical AI use, particularly in customer-facing applications, to comply with regulations (e.g., GDPR, CCPA) and internal ethics policies. Implement systems to detect changes in data patterns (e.g., seasonal changes, topic shifts) that could degrade model performance. Mentor and develop team members, fostering their skills in AI practices, and Data and AI platforms Use feedback to refine model prompts or retrain models, adapting the GenAI application to better serve users Experience with performance monitoring, debugging, and optimizing large-scale GenAI systems Maintain open communication with product managers, engineers, compliance officers, and legal teams to align on goals, especially concerning compliance, ethics, and evolving business needs Prepare reports for leadership, detailing model performance, ethical compliance, and any actions taken to improve application sustainability. This documentation supports transparency and helps inform future decision-making. Deploy and manage MLOps pipelines and monitoring tools to support automated tracking, alerts, and retraining for sustained model quality. Qualifications Required: Bachelor's degree in Computer Science, Information Technology, or a related field; Master's degree preferred. 8+ years of experience in IT, with at least 4 years focused on Leading the application support for AI/ML programs in a production grade. Strong understanding Model Performance Monitoring and Maintenance Work closely with customer support and product teams to gather feedback on model outputs, which can highlight areas for improvement or reveal new user needs. Promote sustainable AI practices by optimizing models and reducing unnecessary compute resources, an increasingly important aspect of AI deployments. Ensure efficient resource use by scaling the infrastructure in response to demand, which optimizes performance and reduces costs, especially in cloud environments. Collaborate with data science teams to retrain or fine-tune models based on new data, customer feedback, or detected data drift, ensuring the model remains up-to-date and effective. Proficiency in scripting languages (e.g., PowerShell, Bash, Python). Preferred: AI and Machine Learning Certifications Ethical AI and Compliance Certifications Cloud and Infrastructure Certifications. Key Competencies Excellent communication and interpersonal skills Ability to collaborate effectively with diverse teams and stakeholders across platforms Strong problem-solving and analytical skills Adaptability and willingness to learn in a rapidly evolving multi-cloud landscape Attention to detail and commitment to quality across different cloud platforms Strategic thinking and ability to align technical solutions with business objectives Excellent time management and organizational skills Ability to work under pressure and manage multiple priorities in a multi-cloud environment. Strong requirements gathering and analysis skills We are looking for an experienced professional who can lead our AI applications that uses our AI platforms, collaborate effectively across teams, and mentor resources to drive excellence in Application support and AI first mindset, particularly in Data and AI platforms. If you have a strong background in AI application support and Observability experience, and a passion for leading and developing teams in a multi-cloud environment, we encourage you to apply.