Utilities AI Engineer: RAG Apps & Cloud Deployments

Accenture; Chicago (IL); On-site; USD 106,000 - 177,800; Full time

Benefits offered by this job

Medical insurance

Dental insurance

Vision insurance

Life insurance

401(k)

Bonus opportunities

Paid holidays

Paid time off

Job summary

Accenture is seeking an AI Engineer to build and integrate AI applications using leading model providers and cloud platforms. You will implement RAG, prompt orchestration, evaluation, and guardrails in production systems, deploying AI workloads with scalability, security, and cost efficiency.

The role requires experience in Python, API integration, vector databases, and orchestration frameworks like LangChain/LlamaIndex, plus DevOps practices such as Docker/Kubernetes and CI/CD.

Qualifications

• Minimum 3 years in software or AI/ML engineering.
• Hands-on building AI applications with providers such as OpenAI, Anthropic, AWS Bedrock, Azure OpenAI, or Google Vertex AI.
• Proficient in Python and API integration; experience with RAG and vector databases.

Responsibilities

• Build AI applications using leading model providers and cloud platforms.
• Implement LLM patterns, RAG, prompt orchestration, evaluation, and guardrails.
• Deploy AI workloads on cloud infrastructure with security and cost efficiency.
• Engineer with modern tooling including LangChain and orchestration frameworks.

Skills

Python

API integration

OpenAI Platform

Anthropic Platform

AWS Bedrock

Azure OpenAI

Google Vertex AI

RAG

LangChain

Vector DB

LlamaIndex

Docker

Kubernetes

Education

Bachelor's degree or equivalent

Tools

Docker

Kubernetes

LangChain

LlamaIndex

AWS Bedrock

Azure OpenAI

Google Vertex AI

Job description

Accenture is seeking an AI Engineer to build and integrate AI applications using leading model providers and cloud platforms. You will implement RAG, prompt orchestration, evaluation, and guardrails in production systems, deploying AI workloads with scalability, security, and cost efficiency.

The role requires experience in Python, API integration, vector databases, and orchestration frameworks like LangChain/LlamaIndex, plus DevOps practices such as Docker/Kubernetes and CI/CD.