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Agentic AI Engineer
Career Insights for Generative Artificial Intelligence Engineer
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Based on Arizona data
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What they do
A Generative Artificial Intelligence Engineer develops, designs, and manages generative models and algorithms that support the generation of new content in the form of images, text, audio, and other multimedia. They utilize GPTs, GANs, VAEs, and other deep learning architectures to craft systems capable of generating data. May work with data scientists, machine learning engineers, and software developers.
$128,751 / year median in Arizona
Job Description
Job Title:
Agentic AI Engineer
•Hiring FAST!
Industry:
Finance Location:
Chandler, AZ Pay Rate:
•HR on W2 Only
•NO C2
C Setting:
Hybrid Required (Remote is NOT an Option)
Duration:
24 months
Job ID:
247937
Required Qualifications:
4+ years of Software Engineering experience. Bachelor's degree in Computer Science, Engineering, or a related technical field (or equivalent experience) Strong experience in software development, system integration, or platform engineering Proficiency in one or more modern programming languages (e.g., Java, Python, C#, or similar) Experience with cloud platforms, distributed systems, and APIs Solid understanding of software design principles, data structures, and system reliability Strong problem solving, communication, and collaboration skills Google Cloud Platform Python ADK Native application build out in Google cloud platforms Low latency microservice build out Agentic AI experience ( Prompting, tooling, Tuning, Guardrails ) Full stack experience is a plus ( React , Java Springboot ) System design experience A Minimum of 3 years experience in relevant areas Operating in Agile environment
Desired Qualifications:
Experience with Generative AI, machine learning platforms, or data driven systems. Preference is for : Google Cloud platforms, Python ADK , Micro Service build out, Lang Chain , Lang Graph , Full Stack development background , Cloud native application experience in google cloud platform, Playbook/Playbook live . Familiarity with cloud-native architectures (microservices, containers, CI/CD) Experience working in regulated or enterprise environments Exposure to DevOps, SRE, or platform engineering practices Leadership experience, mentoring, or technical ownership of complex systems Experience supporting high availability or customer facing platforms Next Generation Agent Product experience Context Engineering Exposure to Multi agent exposure
Responsibilities:
Design, develop, test, and deploy software and platform components aligned with business and architectural standards and Generative AI platforms like GCP Contribute to system architecture and technical design decisions Integrate cloud services, APIs, and data sources to deliver end to end solutions Implement automation, monitoring, and observability to ensure system reliability Collaborate with cross functional partners including product, security, infrastructure, and operations Support production systems through troubleshooting, root cause analysis, and continuous improvements