AI Engineering Consultant - Senior Manager - Consulting

AI Engineering Consultant - Senior Manager - Consulting - Open Location

Location:

Anywhere in Country

At EY, we’re all in to shape your future with confidence. We’ll help you succeed in a globally connected powerhouse of diverse teams and take your career wherever you want it to go. Join EY and help to build a better working world.

Senior Manager in AI Native Engineering to join our Artificial Intelligence and Data team. You will sit side-by-side with clients and diverse teams from EY to create a well-rounded approach to advising and solving challenging problems, applying cutting-edge technology to bring solutions to our clients. You will be responsible for researching, building, and implementing scalable artificial intelligence systems that learn and make predictions tailored to diverse business requirements across environments including cloud and on-premises.

• Enhancing data pipelines and storage to ensure data is clean, accurate, and optimized for XOps processes.
• Monitoring and optimizing learning processes to continuously improve high-performance models.
• Collaborating with data and analytics professionals to industrialize analysis into effective actionable analytics solutions.
• Leading engagement delivery and managing client relationships daily.
• Accountable for program/project management and engagement economics.
• Developing resource plans and budgets for engagements.
• Continuously improving processes by identifying innovative solutions through research and analysis.
• Managing professional employees and supervising teams to deliver complex technical initiatives.
• Engaging actively with clients, participating in daily working sessions, and leading work streams from planning through execution to closure.
• Identifying opportunities for additional services and managing engagement economics.

• Lead teams of AI engineers and data scientists to deliver modern ML and AI solutions for clients.
• Stay current on AI technology trends, industry innovations, and regulatory requirements; provide guidance on Model Ops tools and architectures that integrate with client ecosystems.
• Design and implement Model Ops target architecture for scalable AI deployment and monitoring.
• Collaborate with cross-functional roles to implement and sustain solutions on client platforms.
• Understand clients’ data, AI, and technology landscape, along with business priorities and success measures.
• Build and maintain strong client relationships, deliver high-quality services, and manage large-scale engagements within time and budget.
• Demonstrate collaboration and effective communication with stakeholders in hybrid work environments.
• Solve complex problems using data-driven decision-making and computational thinking.
• Proficiency in deep learning, machine learning, programming, and data architecture design.
• Experience in cloud computing and technical design optimization.
• Strong communication, influence, and negotiation skills.
• Experience developing solutions for complex challenges and recommending policy or process improvements.
• Sound judgment in selecting methods and techniques to achieve results.
• Lead teams effectively and manage organizational change.

• Bachelor’s degree, or MS degree in Business or Economics, Technology Entrepreneurship, Computer Science, Informatics, Statistics, Applied Mathematics, Data Science, or Machine Learning
• 8-10+ years of professional consulting experience in business or technology consulting
• 3-5+ years of experience directly managing technical teams and/or consulting teams
• Experience deploying Generative AI models and frameworks (e.g., OpenAI family, open source LLMs, RAG, Langchain, etc.)
• Experience with ML packages (scikit-learn, PyTorch, ONNX) and Dev Ops tools (Git, Azure Dev Ops, Jira)
• Understanding of ML workflows and MLOps methods and platforms (e.g., MLFlow)
• Strong Python skills; CI/CD and test-driven development experience
• Experience designing and deploying end-to-end ML workflows on major cloud platforms
• Understanding of data structures, data modeling, software engineering best practices
• Proficiency with SQL, Pandas, Spark
• Ability to communicate findings clearly…