Senior AI Engineer: LLM & GenAI Solutions

EY; San Antonio (TX); Hybrid; USD 66,000 - 134,000; Full time

Job summary

EY is seeking an experienced AI/ML Engineer to design, develop and deploy production‑grade AI/ML solutions, including generative AI and intelligent automation, across enterprise platforms. The role emphasizes end‑to‑end pipelines, retrieval augmentation, and agentic components with strong collaboration across engineering and product teams.

You will work in a hybrid EY environment, contributing to secure, scalable AI systems and applying best practices in data quality, observability and release

Qualifications

• Bachelor’s or master’s degree required.
• Minimum of 2 years of related AI/ML engineering experience.
• Able to explain complex AI system behavior to technical and non‑technical stakeholders.
• Strong ownership and accountability for AI systems from design to production.

Responsibilities

• Develop, test, deploy, and support production‑grade AI/ML and automation solutions.
• Solve complex technical problems across development, integration and production support.
• Translate user requirements into technical designs, APIs, workflows, and implementation patterns.
• Build and integrate LLM, RAG, and agentic components into enterprise solutions.
• Support project delivery with disciplined execution, estimation, documentation and risk identification.
• Participate in design reviews with trade‑off analysis and input.
• Use modern AI‑assisted software engineering tools to improve delivery speed and code quality.

Skills

Python

LLM Applications

AI/ML Engineering

API Development

Prompt Engineering

Docker/Kubernetes

LangChain

Retrieval-Augmented eSL

Education

Bachelor’s or Master’s degree

Tools

Azure OpenAI

AWS Bedrock

Google Vertex AI

LangChain

Pinecone

Weaviate

Claude Code

Job description

EY is seeking an experienced AI/ML Engineer to design, develop and deploy production‑grade AI/ML solutions, including generative AI and intelligent automation, across enterprise platforms. The role emphasizes end‑to‑end pipelines, retrieval augmentation, and agentic components with strong collaboration across engineering and product teams.

You will work in a hybrid EY environment, contributing to secure, scalable AI systems and applying best practices in data quality, observability and release