Generative AI Systems Engineer

Accenture PLC; Chicago (IL); On-site; USD 39,000 - 117,000; Full time

Benefits offered by this job

Medical, dental, vision, life

Long-term disability insurance

401(k) plan

Bonus opportunities

Paid holidays

Paid time off

Job summary

Accenture seeks an experienced AI engineer to design and optimize prompts and generative applications built on foundation models. You will architect AI systems, collaborate with cross-functional teams, and guide production-ready pipelines across cloud platforms.

The role emphasizes robust evaluation for safety and fairness, mastering AI frameworks, and delivering scalable ML infrastructure in a dynamic, client-facing environment.

Qualifications

• Minimum 3 years designing and building resilient AI systems or products.
• Experience with RAG and data pipelines.
• Proficient in one or more programming languages (Python/JS/Java/Spring/Go).
• Experience with at least one public cloud (AWS/GCP/Azure).
• 2+ years leading AI-driven projects or teams.
• Bachelor's degree or equivalent work experience.

Responsibilities

• Design, develop, and optimize AI prompts and apps powered by foundation models.
• Architect generative agent systems for multi-model coordination.
• Develop application and component strategies across UX and backend.
• Define and optimize AI system architectures and best practices.
• Lead code reviews and ensure engineering standards.

Skills

AI systems design

Prompt engineering

Python

Java

JavaScript

GoLang

Cloud platforms

LangGraph

Semantic Kernel

Autogen

CI/CD

Education

Bachelor’s degree

Tools

AWS

GCP

Azure

Anthropic

LangGraph

Semantic Kernel

Autogen

Job description

Accenture seeks an experienced AI engineer to design and optimize prompts and generative applications built on foundation models. You will architect AI systems, collaborate with cross-functional teams, and guide production-ready pipelines across cloud platforms.

The role emphasizes robust evaluation for safety and fairness, mastering AI frameworks, and delivering scalable ML infrastructure in a dynamic, client-facing environment.