AmazonAgentic Data Engineer, Frontier AI Tooling
Amazon is hiring an Agentic Data Engineer, Frontier AI Tooling in Seattle, United States. It pays $132k-$179k a year and Level rates it ; you can apply on Level.
AI in this role
You will build and operate the pipelines and datasets that feed the context layer and agentic workflows: ingesting external insights, internal data, and insights collected by sales and delivery teams, and turning them into reliable, well-modeled datasets that models and agents can reason over. You design data models, ETL, and integration services that are flexible, extensible, and scalable, then support and grow them over time. This is a hands-on role where the playbook is written in real time. You ship to production and own the correctness of the data that downstream agents depend on.
You are comfortable with ambiguity and partner with business leaders to build the pipelines that answer their key questions. You will unify fragmented data pipelines, build robust data models, and ensure reliable data lineage across multiple product areas, working closely with software engineers, product managers, and analytics teams. This is a role with high visibility to senior leadership and high opportunity for impact.
Key job responsibilities
- Own end-to-end delivery of data pipelines: design, build, test, deploy, and operate
- Build and optimize ETL/ELT jobs that produce the foundational datasets powering the team's products and agentic workflows
- Model structured and unstructured data (external insights, internal data, sales and delivery insights) so it is queryable and consumable by AI agents at scale
- Design the data structures, schemas, and contracts that downstream services and agents depend on
- Build and own data-quality tooling: validation, reconciliation, anomaly detection, and monitoring so bad data does not reach agents or models
- Ship to production regularly in a high-ambiguity environment, balancing speed against reliability
- Raise operational-excellence hygiene (data tests, monitoring, runbooks) for the pipelines you own
- Write clear data models, pipeline design notes, and runbooks a peer can act on
About the team
ABOUT AWS:
Diverse Experiences
Amazon values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.
Why AWS
Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.
Work/Life Balance
We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud.
Inclusive Team Culture
AWS values curiosity and connection. Our employee-led and company-sponsored affinity groups promote inclusion and empower our people to take pride in what makes us unique. Our inclusion events foster stronger, more collaborative teams. Our continual innovation is fueled by the bold ideas, fresh perspectives, and passionate voices our teams bring to everything we do.
Mentorship and Career Growth
We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.
Basic qualifications
- 3+ years of data engineering experience
- 1+ years of developing and operating large-scale data structures for business intelligence analytics using ETL/ELT processes experience
- 1+ years of developing and operating large-scale data structures for business intelligence analytics using data modeling experience
- Bachelor's degree or foreign equivalent in Computer Science, Engineering, Information Systems, Mathematics, or a related field
- Experience writing and optimizing SQL queries with large-scale, complex datasets
Preferred qualifications
- Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions
- Experience with non-relational databases / data stores (object storage, document or key-value stores, graph databases, column-family databases)
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.
USA, TX, Austin - 132,100.00 - 178,800.00 USD annually
USA, VA, Arlington - 132,100.00 - 178,800.00 USD annually
USA, WA, Seattle - 132,100.00 - 178,800.00 USD annually
How we rate this
Agentic Data Engineer, Frontier AI Tooling at Amazon rates 63 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.
Works on AI. The daily work is on AI products, without building the model.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Also common in data engineer jobs at this level
Pay
- This job starts at
- $132k
- Typical data engineer job
- $145k
This posting starts 9% below the typical data engineer job. See data engineer jobs
Questions you could be asked
- How do you decide when an AI agent can act on its own versus asking for approval first?
- Describe a typical day in a role like this one: which parts run through AI directly?
- If you removed AI from this role, what would be left, and how do you decide what still needs a human?
Adapt your resume
- List these exact terms on your resume: AI agents. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Show where AI is part of your daily process, not a one-off project. This role expects it to be a running habit.
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