1

Artificial Intelligence Engineer Jobs (NOW HIRING)

Our expert teams of physicists, engineers, data scientists and problem-solvers work together with the world's leading technology providers to accelerate the delivery of tomorrow's electronic devices.

next page

Showing results 1-20

Artificial Intelligence Engineer information

See salary details

$44K

$106.4K

$173.5K

How much do artificial intelligence engineer jobs pay per year?

As of Jun 9, 2026, the average yearly pay for artificial intelligence engineer in the United States is $106,386.00, according to ZipRecruiter salary data. Most workers in this role earn between $76,000.00 and $132,500.00 per year, depending on experience, location, and employer.

What are the typical daily responsibilities of an Artificial Intelligence Engineer?

Artificial Intelligence Engineers typically spend their days developing and optimizing machine learning models, analyzing large datasets, and collaborating closely with data scientists, software engineers, and product managers. They design and test algorithms to solve specific business problems, document their findings, and frequently review recent research to stay on top of advances in the field. Additionally, they participate in code reviews, attend project meetings, and may contribute to deploying AI systems into production environments. This role offers a dynamic and intellectually stimulating work environment where continuous learning and innovation are encouraged.

What does an Artificial Intelligence Engineer do?

An Artificial Intelligence Engineer designs, develops, and implements AI models and algorithms to solve complex problems. They work with machine learning, deep learning, natural language processing, and data science to create intelligent systems. Their responsibilities include data preprocessing, model training, deployment, and optimization to enhance AI performance. AI Engineers collaborate with data scientists, software developers, and business teams to integrate AI solutions into real-world applications.

What are the key skills and qualifications needed to thrive in the Artificial Intelligence Engineer position, and why are they important?

To thrive as an Artificial Intelligence Engineer, you need proficiency in programming languages such as Python or Java, a solid background in mathematics and statistics, and experience with machine learning frameworks, often supported by a degree in computer science or a related field. Familiarity with tools like TensorFlow, PyTorch, and cloud platforms (AWS, Azure, or Google Cloud) along with certifications in AI or data science are highly valued. Strong problem-solving abilities, effective communication, and collaborative teamwork skills set standout professionals apart. These competencies are crucial for designing robust AI solutions, integrating them into business processes, and working efficiently within interdisciplinary teams.

What cities are hiring for Artificial Intelligence Engineer jobs? Cities with the most Artificial Intelligence Engineer job openings:
What are the most commonly searched types of Artificial Intelligence Engineer jobs? The most popular types of Artificial Intelligence Engineer jobs are:
Who are the top companies hiring for Artificial Intelligence Engineer jobs? The top employers for Artificial Intelligence Engineer jobs are:
What states have the most Artificial Intelligence Engineer jobs? States with the most job openings for Artificial Intelligence Engineer jobs include:
What job categories do people searching Artificial Intelligence Engineer jobs look for? The top searched job categories for Artificial Intelligence Engineer jobs are:
Infographic showing various Artificial Intelligence Engineer job openings in the United States as of June 2026, with employment types broken down into 100% Contract. Highlights an 100% In-person job distribution, with an average salary of $106,386 per year, or $51.1 per hour.
Artificial Intelligence Engineer

Artificial Intelligence Engineer

InfoPeople Corporation

San Antonio, TX

Full-time

Posted 22 days ago


Job description

Strong systems depth across backend services, integrations, data flows, and application logic Evidence of building internal platforms or workflow systems, not just end-user AI features Clear judgment about deterministic versus model-driven system boundaries Experience with human review, escalation, auditability, and operational safeguards Willingness to work closely with teams to understand real workflows, not just stated requirements built internal platforms, shared services, or workflow systems used by multiple teams designed connectors, integration patterns, tool contracts, or context layers built AI systems for enterprise operations, security-sensitive workflows, compliance-heavy domains, or internal business processes Practical daily use of LLMs as building tools