AI Engineering Consultant - Senior Manager - Consulting - Open Location

EY•Hartford, DC

2d•$144,000 - $374,000•Remote

About The Position

EY delivers unparalleled cross functional tech consulting services in artificial intelligence, machine learning, generative AI, agentic AI, and cloud engineering. We always support and enable big ideas with the ambition to keep doing more. We leverage leading practices and a high degree of business acumen that has been compiled over years of experience to ensure the highest level of execution and satisfaction for our clients. Our Artificial Intelligence and Data 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. Come help define the future of AI. EY is significantly investing in their award-winning AI, Data & Engineering practice. You will help our clients develop and realize their ambition to leverage AI at scale and drive better business outcomes. You will work with a wide variety of clients to deliver the latest data science and big data 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 consulting services to ensure AI solutions are properly engineered and maintained to support the ongoing business needs of our clients. This is a high growth area and a high visibility role with plenty of opportunities to enhance your skillset and build your career. We are looking for leaders who connect AI strategy to the engineering, deployment, and scaling of AI and Machine Learning Operations capabilities.

Requirements

Bachelor’s degree, or MS degree in Business or Economics, Technology Entrepreneurship, Computer Science, Informatics, Statistics, Applied Mathematics, Data Science, or Machine Learning
Minimum of 8-10+ years of professional consulting experience in business or technology consulting or similar roles
Minimum of 3-5+ years of experience directly managing technical teams and/or consulting teams
Experience using and managing the deployment of foundation models, generative AI, and agentic AI frameworks e.g. OpenAI family, open source LLMs, Dall-e, LlamaIndex, Langchain, Retrieval Augmented Generation (RAG).
Experience working with popular ML packages such as scikit-learn, Pytorch and ONNX, or related ML libraries.
Extensive experience using DevOps tools like GIT, Azure Devops and Agile tools such as Jira to develop and deploy analytical solutions with multiple features, pipelines, and releases.
A solid understanding of Machine Learning (ML) workflows including ingesting, analysing, transforming data and evaluating results to make meaningful predictions.
Experience with MLOps, LLMOps, and AgentOps methods and platforms such as MLFlow.
Strong skills in Python.
Experience with CI/CD and test-driven development.
Experience designing, building, evaluating, deploying, and maintaining ML models, generative AI systems, agentic workflows, frameworks, and pipelines.
Experience designing and deploying end to end ML workflows on at least one major cloud computing platform.
Understanding of data structures, data modelling and software engineering best practices.
Proficiency using data manipulation tools and libraries such as SQL, Pandas, and Spark.
Clearly communicating findings, recommendations, and opportunities to improve data systems and solutions.
Experience with containerization and scaling models.
Willingness to travel to meet client obligations.
Strong knowledge of AI technologies, Responsible AI, evaluation methods, and frameworks
Excellent analytical, problem-solving, and communication skills, with the ability to articulate complex technical concepts to non-technical stakeholders
Demonstrated leadership and project management experience, with the ability to lead multidisciplinary teams and drive successful outcomes
Team player

Nice To Haves

Experience in leading business or IT transformation projects that have supported data science, business intelligence, artificial intelligence, and cloud applications at scale
Familiarity with regulatory frameworks and standards related to AI ethics, privacy, and data protection
Working experience with Agile and/or Scrum methods of delivery
Working experience with design led thinking
Microsoft, Databricks, AWS, NVIDIA or Snowflake Certifications in the Data & AI domain
A deep understanding of and ability to teach concepts, tools, features, functions, and benefits of different approaches to apply them.
Master's degree Computer Science, Mathematics, Physical Sciences, or other quantitative field.
Strong skills in languages beyond Python: R, JavaScript, Java, C++, C.
Experience fine-tuning Generative AI models.

Responsibilities

Translating AI strategy into a scalable Model Engineering roadmap that aligns with the client’s goals, mission and vision
Leading teams of AI engineers and data scientists in delivery of production-grade machine learning, generative AI, and agentic AI solutions for clients
Staying abreast of AI technology trends and provide directional guidance and recommendations around MLOps, LLMOps, and AgentOps tools and solutions that fit their needs and integrate with their existing ecosystem
Applying combined business and technical knowledge to develop and execute ModelOps target architecture that enables implementation and monitoring of AI at scale
Collaborating with Data Scientists, Data Engineers, Cloud Engineers, MLOps, LLMOps, and platform engineers, DevOps to implement and sustain solutions in the client’s platform of choice
Staying abreast of industry trends, technology innovations and AI regulatory requirements across the globe
Understanding clients’ overall data, AI and technology landscape and business priorities and success measures
Strong team collaboration and experience working with a diverse team in a hybrid model (on site and remote)
Working on large-scale client engagements. Fostering relationships with client personnel at appropriate levels. Consistently delivering quality client services. Driving high-quality work products within expected timeframes and on budget
Collaborating, influencing and building consensus through constructive relationships and effective listening
Solving problems by incorporating data into decision making