AI Delivery Leader
3 days ago
Atlanta
We are seeking an experienced AI Delivery Leader to lead the successful delivery of enterprise-scale Artificial Intelligence (AI) and Machine Learning (ML) initiatives. This role will be responsible for driving the end-to-end execution of AI programs—from strategy and solution design through deployment, adoption, and continuous optimization. The ideal candidate combines strong AI/ML technical expertise with proven leadership in program delivery, stakeholder management, and digital transformation. \n \n Key Responsibilities \n AI Strategy & Solution Delivery \n\n • Lead the execution of enterprise AI/ML initiatives aligned with business objectives and digital transformation strategies.\n, • Translate complex business challenges into scalable AI-driven solutions and define delivery roadmaps.\n, • Establish delivery standards, governance frameworks, and best practices for AI solution implementation.\n\n Program & Delivery Management \n\n • Own the complete lifecycle of AI programs, including ideation, design, development, deployment, and production support.\n, • Manage project scope, timelines, budgets, risks, dependencies, and resource planning.\n, • Ensure projects are delivered on schedule, within budget, and with measurable business outcomes.\n\n Stakeholder Management \n\n • Partner with executive leadership, business stakeholders, product owners, and technical teams to define priorities and success criteria.\n, • Provide regular executive-level updates on project progress, risks, milestones, and outcomes.\n, • Serve as the primary liaison between business and technical organizations.\n\n Technical Leadership \n\n • Provide architectural guidance for AI/ML solutions, MLOps, cloud platforms, and deployment strategies.\n, • Promote best practices across data engineering, model development, testing, deployment, monitoring, and lifecycle management.\n, • Drive continuous improvement of model performance, scalability, reliability, and operational efficiency.\n\n People Leadership \n\n • Build, mentor, and lead high-performing cross-functional teams comprising Data Scientists, Machine Learning Engineers, Data Engineers, and Business Analysts.\n, • Foster an Agile, collaborative, and innovation-focused culture.\n, • Support capability development through coaching, knowledge sharing, and adoption of emerging AI technologies.\n\n Governance & Responsible AI \n\n • Ensure AI solutions comply with organizational governance standards and regulatory requirements.\n, • Promote responsible AI practices, including fairness, explainability, bias mitigation, privacy, and security.\n, • Maintain compliance with enterprise data governance and industry regulations.\n\n Required Qualifications \n\n • Bachelor's or Master's degree in Computer Science, Data Science, Engineering, or a related discipline.\n, • 10+ years of technology delivery experience, including 3–5 years leading enterprise AI/ML programs.\n, • Proven experience delivering AI/ML solutions from concept through production deployment.\n, • Strong knowledge of AI/ML frameworks, cloud platforms (AWS, Azure, or GCP), and modern data ecosystems.\n, • Demonstrated success leading large-scale, cross-functional technology initiatives.\n\n Preferred Qualifications \n\n • Experience with MLOps platforms and end-to-end model lifecycle management.\n, • Hands-on experience with Generative AI, Large Language Models (LLMs), NLP, or advanced analytics solutions.\n, • Cloud or AI/ML certifications (AWS, Azure, GCP, Databricks, etc.).\n, • Experience in consulting, enterprise transformation, or large-scale digital modernization programs.\n\n Required Skills \n\n • AI & Machine Learning Program Delivery\n, • AI Strategy & Digital Transformation\n, • Program & Project Management (Agile/Scrum)\n, • AI Solution Architecture\n, • MLOps & Model Lifecycle Management\n, • Cloud Platforms (AWS, Azure, GCP)\n, • Generative AI & NLP\n, • Data Engineering & Analytics\n, • Executive Stakeholder Management\n, • Cross-functional Team Leadership\n, • Risk, Budget & Resource Management\n, • Governance, Security & Responsible AI\n, • Excellent Communication & Presentation Skills\n\n Success Measures \n\n • Successful deployment and enterprise adoption of AI solutions.\n, • Delivery of measurable business outcomes, including ROI, productivity improvements, and operational efficiencies.\n, • Consistent on-time and within-budget execution of AI initiatives.\n, • High stakeholder satisfaction and executive engagement.\n, • Continuous improvement in AI delivery maturity, governance, and organizational capability.\n