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RWJBarnabas Health

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RWJBarnabas Health

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Inficare Technologies

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RWJBarnabas Health

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RWJBarnabas Health

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RWJBarnabas Health

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Share this job: Share: Share AI Data Engineer - Senior Consultant with Facebook Share AI Data Engineer - Senior Consultant with LinkedIn Share AI Data Engineer - Senior Consultant with Twitter ...

Deloitte

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Huntsville, AL · On-site

$112K - $135K/yr

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How much do ai data engineer jobs pay per year?

As of Jun 8, 2026, the average yearly pay for ai data engineer in the United States is $129,716.00, according to ZipRecruiter salary data. Most workers in this role earn between $114,500.00 and $137,500.00 per year, depending on experience, location, and employer.

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

To thrive as an AI Data Engineer, you need strong proficiency in programming (Python, SQL), data architecture, and machine learning fundamentals, typically supported by a degree in computer science, engineering, or a related field. Experience with big data tools (Spark, Hadoop), cloud platforms (AWS, Azure, GCP), and certifications like Google Professional Data Engineer are highly valuable. Excellent problem-solving skills, attention to detail, and effective team communication help distinguish top performers in this role. These abilities ensure the development of robust data pipelines and systems that power accurate AI solutions in a collaborative and rapidly-evolving environment.

What does an AI Data Engineer do?

An AI Data Engineer designs, builds, and manages data pipelines and infrastructure to support AI and machine learning models. They collect, process, and store large datasets, ensuring data is clean, structured, and accessible for AI applications. Their role involves working with big data tools, cloud platforms, and databases to optimize performance and scalability. Collaboration with data scientists and software engineers is essential to deploy and maintain AI solutions efficiently.

What are some common challenges an AI Data Engineer might face in their daily work?

AI Data Engineers often encounter challenges such as integrating data from diverse sources, ensuring data quality and consistency, and building scalable data pipelines to handle large volumes of information. Working closely with data scientists and software engineers requires strong collaboration and flexibility to adapt to shifting project requirements or algorithms changes. Keeping up with the latest developments in big data and machine learning tech stacks is also crucial. Overcoming these challenges provides a dynamic work environment and offers valuable learning and career growth opportunities.

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Ai Data Engineer jobs near you

AI Data Engineer

Atonom

Provo, UT • On-site

Full-time

Medical, PTO

Posted 11 days ago

Job description

Salary: $50,000 to $90,000

AI Data Engineer

ABOUT ATONOM

Atonom.ai builds Cloud Employees: intelligent AI agents that execute complex work across Sales, Marketing, Support, and HR. We believe growth should be limited by ambition, not headcount. We move beyond simple automation to genuine autonomy, empowering businesses to scale instantly. Join us as we build the infrastructure for the next generation of work.

THE ROLE

As a AI Data Engineer, you'll work alongside senior team members to configure, deploy, and optimize AI Cloud Employees for our customers. This is a hands-on role where you'll learn quickly, work directly with clients, and see the impact of your work from day one. You don't need years of experience. You need curiosity, technical aptitude, and the drive to figure things out.

WHAT YOU'LL DO

Configure and deploy AI Cloud Employees for customers, with a focus on data integrations, API connections, and workflow logic.
Join client calls to understand data environments and help translate business needs into AI workflows, including prompt design, data mappings, and QA checks.
Troubleshoot data and integration issues with support from senior team members. Trace problems, find root causes, and work toward solutions.
Document data patterns, integration playbooks, and technical reference materials that help the whole team move faster.
Share product feedback with Engineering and Product teams, including data handling gaps, integration limitations, and customer pain points.

WHO YOU ARE

Recent graduate (or soon to be) in Computer Science, Data Science, Software Engineering, Information Systems, or a related technical field. Self-taught candidates with a strong portfolio are also welcome.
Comfortable working with data. Maybe you've written SQL queries, built a small pipeline, worked with APIs, or cleaned up messy datasets in a class or side project.
Interested in LLMs and prompt engineering. You don't need to be an expert, but you've explored how AI models work beyond surface-level usage.
A clear communicator who can walk non-technical teammates and clients through technical concepts without jargon.
Self-directed and low-ego. You ask good questions, take feedback well, and move fast in ambiguous situations.

YOUR FIRST 90 DAYS

Month 1: Learn the Atonom platform inside and out. Shadow senior team members on client calls and implementations. Get certified on internal tooling.
Month 2: Take ownership of your first customer implementations with senior support. Begin contributing to internal documentation and playbooks.
Month 3: Run implementations with increasing independence. Present learnings and customer pain points to the Product team.

TECHNICAL SKILLS (NICE TO HAVE)

Exposure to workflow automation tools (Zapier, Make, or similar).
Basic understanding of APIs, webhooks, or data integrations.
Familiarity with SQL, Python, or JavaScript.
Experience with CRMs like Salesforce or HubSpot.
Any hands-on project involving LLMs or prompt engineering (personal, academic, or professional).

WHY JOIN

Real AI work. Not research papers. Production agents that generate measurable ROI for real businesses.
Mentorship built in. Learn from experienced specialists who invest in your growth.
Career velocity. High-visibility role with clear paths toward Solutions Architecture, Product, or Team Leadership.
Impact from day one. Small team, fast shipping, your contributions matter immediately.

BENEFITS

PTO accrual starts on day one.
Competitive health benefits package.
Paid holidays and company events.
Competitive salary.