IT Project Manager (AI)

Overview

Direct message the job poster from Norconsult Telematics

As the AI-Focused Application Development Project Manager, you will spearhead the delivery of complex application development projects with a strong emphasis on artificial intelligence (AI) and data analytics, driving the organization’s digital transformation and AI innovation goals. Your primary objective is to lead end-to-end project execution, utilizing Agile, Scrum, and Lean methodologies to ensure timely delivery, cost efficiency, and high-quality outcomes. You will foster collaboration across Cross-functional teams, manage stakeholder relationships, mitigate risks, and champion AI-driven solutions to enhance operational efficiency, customer experiences, and business value.

Responsibilities

• AI-Centric Project Leadership : Plan, manage, and deliver application development and AI-driven projects from initiation to closure, ensuring alignment with strategic objectives, on-time delivery, and budget adherence using Agile, Scrum, or Lean frameworks.
• AI and Digital Transformation : Lead initiatives to develop and deploy innovative AI-powered applications and analytics solutions, integrating machine learning models, generative AI, and data visualization tools to optimize business processes and enhance customer experiences.
• Team Leadership : Mentor and guide cross-functional teams, including AI engineers, data scientists, developers, and IT specialists, fostering a collaborative environment and ensuring optimal resource utilization for AI project success.
• Stakeholder Engagement : Act as the primary point of contact for stakeholders, delivering clear, AI-driven insights through reports and presentations to communicate project progress, model performance, and strategic recommendations.
• Risk Management and Compliance : Develop and implement risk management plans tailored to AI project challenges, ensuring compliance with ISO standards, ethical AI guidelines, and data privacy regulations while maintaining business continuity.
• Innovation and AI Process Optimization : Drive process improvements by adopting cutting-edge AI tools, frameworks (e.g., TensorFlow, PyTorch), and methodologies to enhance application development, AI model deployment, and analytics workflows.
• Data-Driven and AI-Enhanced Decision Making : Leverage AI models and analytics to generate actionable insights, monitor KPIs, and support strategic business decisions, ensuring robust model evaluation and performance tracking.

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