Senior Manager, Forward-Deployed AI Engineer (Consulting)

EY; Secaucus (NJ); Hybrid; USD 144,000 - 329,000; Full time

Benefits offered by this job

Total Rewards package including health

Job summary

EY is recruiting a Forward Deployed Engineer Senior Manager in the US. You will lead diverse client teams to design, build and deploy scalable AI/ML solutions across data platforms and environments.

You will translate AI strategy into engineering programs, guide MLOps/LLMOps implementations, and work with cross‑functional teams to deliver measurable business value. A hybrid work model is supported.

Qualifications

• Bachelor’s degree or MS in a related field.
• 8–10+ years professional consulting experience.
• 3–5+ years of managing technical/consulting teams.
• Experience deploying foundation models, generative AI, and agentic AI frameworks.
• Proficiency with ML packages (scikit-learn, PyTorch, ONNX).
• Experience with CI/CD and DevOps practices.
• Strong Python and data engineering capabilities.
• Willingness to travel to client locations.

Responsibilities

• Lead lean, client-embedded AI engineering teams delivering production-grade ML solutions.
• Diagnose opportunities, shape, engineer, and operationalize AI strategies at scale.
• Establish ModelOps and agentic architectures for governance and cost‑management.
• Collaborate with Data Scientists, Cloud Engineers, MLOps, LLMOps and platform engineers.
• Provide guidance on AI toolchains (Claude, Codex, GitHub, and related MLOps tools).
• Develop reusable engineering patterns and scalable accelerators.

Skills

Python

DevOps

CI/CD

GIT

Azure DevOps

Jira

Docker

Kubernetes

ML Frameworks

ModelOps

LLMOps

AgentOps

Cloud Platforms

Education

Bachelor’s degree, or MS degree in Computer Science, Data Science, or ML

Master’s degree in Computer Science, Mathematics, or quantitative field

Tools

GIT

Azure DevOps

Jira

Docker

Kubernetes

MLFlow

Langchain

Job description

EY is recruiting a Forward Deployed Engineer Senior Manager in the US. You will lead diverse client teams to design, build and deploy scalable AI/ML solutions across data platforms and environments.

You will translate AI strategy into engineering programs, guide MLOps/LLMOps implementations, and work with cross‑functional teams to deliver measurable business value. A hybrid work model is supported.