Forward-Deployed AI Engineering Leader – Senior Manager

EY; St. Louis (MO); Hybrid; USD 144,000 - 359,000; Full time

Job summary

EY is expanding its AI, Data & Engineering practice in the US. The Forward Deployed Engineer Senior Manager will lead lean, client-embedded teams to diagnose opportunities, design scalable AI solutions, and translate strategy into production-grade ML, generative AI, and agentic AI deployments for diverse clients.

You will collaborate with Data Scientists, Cloud Engineers, and DevOps to operationalize AI at scale, stay current on AI trends and regulatory requirements, and drive measurable

Qualifications

• Bachelor’s degree, or MS degree in Business or Economics, Technology Entrepreneurship, Computer Science, Informatics, Statistics, Applied Mathematics, Data Science, or Machine Learning
• Minimum 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 identifying, solutioning, designing, building, evaluating, deploying, operating, measuring value from, and expanding 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, earn executive client trust, shape commercial opportunities, and drive measurable outcomes
• Team player

Responsibilities

• Lead lean, client-embedded AI engineering teams to diagnose opportunities and scale AI strategy.
• Deliver production-grade ML, generative AI, and agentic AI solutions for diverse clients.
• Lead opportunity qualification, solution demonstrations, proposals, and delivery economics for forward-deployed AI engineering work.
• Establish evaluation, observability, security, and cost-management standards for production agentic systems.
• Collaborate with data engineers, cloud engineers, MLOps, and platform engineers to implement solutions in the client’s platform of choice.
• Provide technical guidance and knowledge sharing across diverse team members.
• Stay abreast of industry trends, AI regulatory requirements, and client landscape.

Skills

Python

DevOps

Jira

MLOps/LLMOps/AgentOps

Cloud platforms

Data science workflows

Education

Bachelor’s degree or MS in a quantitative field

Tools

OpenAI models

Docker

Kubernetes

Git

Azure DevOps

Pandas / Spark (data libs)

Job description

EY is expanding its AI, Data & Engineering practice in the US. The Forward Deployed Engineer Senior Manager will lead lean, client-embedded teams to diagnose opportunities, design scalable AI solutions, and translate strategy into production-grade ML, generative AI, and agentic AI deployments for diverse clients.

You will collaborate with Data Scientists, Cloud Engineers, and DevOps to operationalize AI at scale, stay current on AI trends and regulatory requirements, and drive measurable