AI Engineering Manager - LLM & Production Systems

EY; San Antonio (TX); On-site; USD 76,000 - 174,000; Full time

Benefits offered by this job

Medical and dental coverage

Pension and 401(k)

Paid time off

Job summary

EY in the United States is seeking a senior AI/ML delivery leader to drive design, development, and delivery of AI-enabled solutions for large enterprise clients. You will own the implementation of AI/ML capabilities, ensure reliability, scalability, and integration with existing platforms, and lead cross-functional teams across engineering, product, risk, and audit.

The role emphasizes production-grade AI systems, CI/CD, observability, and governance, with hands-on engineering, architecture

Qualifications

• Bachelor's or master's degree in a relevant field.
• Minimum of 6 years of applied engineering experience in AI/ML roles.
• Clear communicator who explains AI system behavior to technical and non-technical stakeholders.

Responsibilities

• Lead design, development, testing, deployment, and support for production-grade AI/ML and generative AI solutions.
• Solve complex technical problems through coding, debugging, testing, and design remediation.
• Integrate LLM, RAG, and agentic components into enterprise applications and platforms.
• Contribute to system design across services, data flows, security controls, and external integrations.
• Lead workstreams and delivery oversight with planning, coordination, and stakeholder communication.
• Drive engineering quality via coding standards, CI/CD, automated testing, observability, and documentation.

Skills

AI/ML engineering

Python

Leadership

Cloud platforms

Education

Bachelor's degree

Tools

Python

LangChain

Azure OpenAI

Kubeflow

Job description

EY in the United States is seeking a senior AI/ML delivery leader to drive design, development, and delivery of AI-enabled solutions for large enterprise clients. You will own the implementation of AI/ML capabilities, ensure reliability, scalability, and integration with existing platforms, and lead cross-functional teams across engineering, product, risk, and audit.

The role emphasizes production-grade AI systems, CI/CD, observability, and governance, with hands-on engineering, architecture