AI Engineering Consultant - Senior Manager - Consulting

AI Engineering Consultant – Senior Manager – Consulting – Open Location

Join to apply for the AI Engineering Consultant – Senior Manager – Consulting – Open Location role at EY
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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 build a better working world.

Our team is focused on artificial intelligence, and we are dedicated to pushing the boundaries of what’s possible. We thrive on collaboration, creativity, and a commitment to excellence. Our Senior Manager, AI Native Engineering, will lead the transformation of data into actionable insights and scalable solutions.

As part of the Artificial Intelligence and Data team, you will work side‑by‑side with clients and EY professionals to create well‑rounded approaches to advising and solving challenging problems. You will build knowledge that can be applied across a wide range of projects now and in the future, while staying ahead of trends and influencing new ways of working.

• Research, build, and implement scalable AI systems that learn and make predictions tailored to diverse business requirements.
• Enhance data pipelines and storage to ensure data is clean, accurate, and optimized for XOps processes.
• Monitor and optimize learning processes to continuously improve high‑performance models.
• Collaborate with data and analytics professionals to industrialize analysis into actionable analytics solutions.
• Lead engagement delivery, manage client relationships, and maintain a focus on quality and risk management.
• Accountable for program/project management, engagement economics, and developing resource plans and budgets.
• Manage professional employees, supervise teams, and deliver complex technical initiatives with accountability for performance and results.
• Engage actively with clients, participate in daily working sessions, and lead work streams from planning through execution to closure.
• Identify opportunities for additional services and manage 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.
• Apply combined business and technical knowledge to design and implement Model Ops target architecture for scalable AI deployment.
• Collaborate effectively with cross‑functional roles—Data Scientists, Engineers (Data, Cloud, MLOps, Dev Ops).
• Build and maintain strong client relationships, deliver high‑quality services, and manage large‑scale engagements within time and budget.
• Demonstrate strong collaboration and consensus‑building skills, fostering constructive relationships in hybrid work environments.
• Use deep learning, machine learning, programming, and data architecture design to solve complex problems.
• Proficiency in Python, cloud computing, Dev Ops tools, CI/CD, and test‑driven development.
• Strong communication skills, ability to influence stakeholders, negotiate with confidence, and convey complex technical concepts to non‑technical audiences.
• Leadership and project management experience, capable of leading multidisciplinary teams and driving successful outcomes.

• Bachelor’s degree or MS in Business, Economics, Computer Science, Statistics, Applied Mathematics, Data Science, or Machine Learning.
• 8–10+ years of professional consulting experience in business or technology consulting.
• 3–5+ years managing technical or consulting teams.
• Experience using and deploying generative AI models (OpenAI family, LLMs, Dall‑e, Llama Index, Langchain, Retrieval Augmented Generation).
• Experience with popular ML packages (scikit‑learn, PyTorch, ONNX) and Dev Ops tools (Git, Azure Dev Ops, Jira).
• Solid understanding of ML workflows and MLOps platforms such as MLflow.
• Strong skills in Python, SQL, Pandas, Spark, and data manipulation tools.
• Experience designing, building, and deploying end‑to‑end ML pipelines on a major cloud…