Skip to main content
Tallo logoTallo logo

Find Jobs

Find Jobs Near You – Available Work in Your Location

Skip to job details

Back to Results

Apply for this opportunity

To apply for this job, you'll continue to an external website or email application.

Robert Half

Artificial Intelligence (AI) Engineer

Career Insights for Artificial Intelligence Engineer (General)

See where this job fits in the broader career landscape. Knowing your career path helps you see what's possible from here.

Scorecard

Based on Georgia data

Review key factors to help you decide if this role fits your goals. How is this calculated?

Were these scores useful?

What they do

An Artificial Intelligence Engineer develops, tests, and deploys artificial intelligence models. May work closely with data software engineers and data professionals to train and implement AI models into existing systems or develop new applications.

$119,867 / year median in Georgia

Explore Career

Job Description

We are looking for an Artificial Intelligence (AI) Engineer to help build and expand practical AI capabilities for the business. This role works closely with functional leaders to uncover meaningful use cases, convert operational challenges into scalable technical solutions, and deliver tools that improve decision-making and efficiency. It is a strong opportunity for a hands-on specialist who enjoys working in a developing environment and wants to influence how AI is applied across the organization.
Responsibilities:
  • Partner with business leaders to understand operational pain points and identify where AI can create measurable value.
  • Translate business needs into solution concepts, technical approaches, and implementable AI initiatives.
  • Design, develop, test, and deploy AI and machine learning applications that address real-world business problems.
  • Evaluate repetitive workflows and manual tasks across departments to recommend automation or intelligent assistance opportunities.
  • Collaborate with teams such as finance, recruiting, and operations to create tools that improve productivity and information flow.
  • Help establish an internal pipeline of AI initiatives by assessing impact, feasibility, and implementation priorities.
  • Serve as a bridge between non-technical stakeholders and technical execution by clearly communicating options, risks, and outcomes.
  • Contribute to the growth of the organization's AI capability through hands-on development, experimentation, and continuous improvement.