Senior AI Developer – GenAI & Data Solutions

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

Benefits offered by this job

Medical and dental coverage

Pension and 401(k)

Paid time off

Hybrid work model

Flexible vacation policy

Job summary

EY is seeking an AI/ML engineer to deliver production‑grade AI/ML, generative AI, and intelligent automation solutions across enterprise platforms. You will design, develop, test, deploy, and support end‑to‑end AI pipelines, translate requirements into solid designs, and contribute to integration of AI capabilities into broader solutions.

The role emphasizes strong software engineering in Python, containerization with Docker and Kubernetes, cloud deployment, and prompt engineering.

Qualifications

• Bachelor's or master's degree required in a relevant field.
• Minimum 2 years in AI/ML engineering roles.
• Ability to explain AI system behavior to technical and non-technical stakeholders.
• Strong ownership from design through production and issue resolution.

Responsibilities

• Develop, test, deploy, and support production‑grade AI/ML, generative AI, and intelligent automation solutions.
• 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, documentation, and risk identification.
• Participate in design reviews and provide trade‑off analyses.

Skills

Python programming

AI/ML engineering

Prompt engineering

LLM integration

RESTful APIs

Education

Bachelor's or Master's degree in a relevant field

Tools

Docker

Kubernetes

LangChain

Pinecone

Weaviate

Azure OpenAI

AWS Bedrock

Google Vertex AI

Job description

EY is seeking an AI/ML engineer to deliver production‑grade AI/ML, generative AI, and intelligent automation solutions across enterprise platforms. You will design, develop, test, deploy, and support end‑to‑end AI pipelines, translate requirements into solid designs, and contribute to integration of AI capabilities into broader solutions.

The role emphasizes strong software engineering in Python, containerization with Docker and Kubernetes, cloud deployment, and prompt engineering.