AI & Machine Learning Engineering Consultant - Databricks - Manager - Consulting- Location OPEN

Summary

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.

The opportunity

Our AI, Data & Engineering team helps apply cutting edge technology and techniques to bring solutions to our clients. As part of that, you'll sit side-by-side with clients and diverse teams from EY to create a well-rounded approach to advising and solving challenging problems, some of which have not been solved before. No two days will be the same, and with constant research and development, you'll find yourself building knowledge that can be applied across a wide range of projects now, and in the future. You'll need to have a passion for continuous learning, stay ahead of the trends, and influence new ways of working so you can position solutions in the most relevant and innovative way for our clients. You can expect heavy client interaction in a fast-paced environment and the opportunity to develop your own career path for your unique skills and ambitions.

EY is experiencing significant growth in consulting services centered on Databricks, a market-leading data and AI platform. We are seeking an accomplished leader who combines strong business acumen, consulting experience, and technical credibility to help clients realize value from this strategic platform. In this role, you will collaborate with clients and Databricks account, sector, and leadership teams to shape and deliver generative AI use cases, advanced data and AI solutions, and scalable platforms.

In this role, you will research, build, and implement scalable AI, machine learning, generative AI, and agentic systems that learn, reason, and generate outputs tailored to business requirements on Databricks. You will enhance data pipelines and storage on Databricks, ensuring data is clean, accurate, and optimized for XOps processes. Additionally, you will monitor and evaluate learning processes to continuously improve high-performance models, collaborating with other data and analytics professionals to industrialize analysis into effective analytics solutions. You will deliver solutions on Databricks, from data pipelines to agents in production.

Your key responsibilities

As a Manager in Model Engineering, you will play a pivotal role in delivering innovative solutions that drive business success. You will work with a wide variety of clients to deliver modern AI engineering, machine learning, and generative AI technologies. Your teams will design and build scalable solutions that unify, enrich, and derive insights from varied data sources across a broad technology landscape. You will help our clients navigate the complex world of modern data science, analytics, and software engineering. We'll look to you to provide guidance and perform technical development tasks to ensure AI solutions are responsibly engineered, evaluated, deployed, and maintained to support the ongoing business needs of our clients.

You will be joining a dynamic and interdisciplinary team of scientists and engineers who love to tackle the most challenging computational problems for our clients. We love to think creatively, build applications efficiently, and collaborate in both the ideation of solutions and the pursuit of new opportunities. Many on our team have advanced academic degrees or equivalent experience in industry.

Your responsibilities will include:

+ Leading AI workstreams from solution design through production deployment and ongoing optimization, focusing on the Databricks platform

+ Leading teams building data engineering pipelines, AI solutions (machine learning, generative AI, and agentic AI), and the pipelines that support AI solutions on Databricks

+ Continuously improving processes by identifying innovative solutions through research and analysis

+ Managing multidisciplinary teams to deliver complex AI engineering initiatives, with accountability for quality, responsible deployment, and results

+ Engaging actively with clients, participating in daily working sessions, and leading workstreams from planning through execution to closure

+ Designing, building, and governing domain ontologies and semantic models that define business concepts, relationships, and rules for AI solutions, knowledge graphs, and enterprise data products

+ Applying a product-centric development approach by partnering with product, business, data science, and engineering stakeholders to define user needs, prioritize reusable capabilities, and iteratively deliver measurable outcomes across the product lifecycle

+ Identifying opportunities for additional services and managing engagement economics

Skills and attributes for success

To excel in this role, you will need a blend of technical expertise and strong interpersonal skills. This role will work to deliver tech at speed, innovate at scale and put humans at the center. Provide technical guidance and share knowledge with team members with diverse skills and backgrounds. Consistently deliver quality client services focusing on more complex, judgmental and/or specialized issues surrounding emerging technology. Demonstrate technical capabilities and professional knowledge. Learn about EY and its service lines and actively assess and present ways to apply knowledge and services

The following attributes will make a significant impact:

+ Translating AI strategy into a implementable Model Engineering activities that aligns with the client's goals, mission and vision

+ Leading teams of AI engineers, data engineers, and data scientists in the delivery of production-grade solutions for clients on Databricks; These include data engineering pipelines, AI solutions (machine learning, generative AI, and agentic AI), and the pipelines that support AI solutions

+ Implementing product-centric AI solutions on Databricks, from discovery and roadmap definition through iterative delivery, adoption, and continuous improvement, with measurable business and user outcomes.

+ Working across design, build, deploy, and operate phases to deliver production-grade data and AI pipelines, governed business ontologies, and semantic models on Databricks, ensuring solutions are reliable, reusable, and aligned with client business processes

+ Experience applying a product-centric development approach to data and AI solutions by defining user outcomes, prioritizing reusable capabilities, managing roadmaps and backlogs, incorporating user feedback, measuring adoption and business value, and continuously improving products after launch

+ Staying abreast of AI technology trends and provide directional guidance and recommendations around AIOps, MLOps, and AgentOps tools and solutions on Databricks that fit their needs and integrate with their existing ecosystem

+ Applying combined business and technical knowledge to develop and execute ModelOps target architecture on Databricks that enables implementation and monitoring of AI at scale, with tools like Unity Catalog and Model Serving

+ Collaborating with Data Scientists, Data Engineers, Cloud Engin...