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AI Data Engineer, Ring/Blink Customer Service Engineering and Insights
- Hawthorne, California, United States
- Hawthorne, California, United States
À propos
The team has a clear AI vision, active prototypes, and an engineering culture where everyone already uses AI in their daily work. Your job is to take ideas to production, keep them reliable, expand to new use cases, and own what you ship. You'll build fast, ship often, and iterate based on real user feedback.
The team uses a mix of AI tools — some running locally for individual productivity, others deployed in the cloud for scalability and broader user access. You'll work across both: building AI agents and tools that range from developer-facing automation to user-facing analytics products.
You'll work alongside data engineers, platform engineers, and BI engineers who own the underlying data infrastructure and dashboards. You own the AI-powered layer on top — the part that makes data accessible, answers trustworthy, and users self-sufficient.
Key job responsibilities Build AI-Powered Data Products (45%) Business users shouldn't need to file a ticket to get answers. You build the tools that make them independent.
Build and deploy conversational analytics agents that let users query CS data in natural language
Productionize AI teammates and agents for specific use cases — transcript analysis, metrics Q&A, contact summarization, pipeline monitoring — using internal platforms and cloud-hosted agent frameworks
Wire together the full stack: data sources (Redshift, S3) → AI layer (LLMs, agents, semantic logic) → user interface
Own the end-to-end delivery: from prototype handoff through production deployment, user onboarding, and iteration
Ensure Correctness & Governance (25%) AI tools that give wrong answers are worse than no tools at all. You make them trustworthy.
Build validation mechanisms — does the AI answer match the source of truth?
Define and maintain the semantic layer: metric definitions, business logic, allowed data scope
Design guardrails: what data can AI access, what questions are in scope, how to handle uncertainty
Own the permission architecture for AI tools (user groups, access policies, cross-account controls)
Implement confidence scoring, audit trails, and feedback loops
Maintain, Monitor & Scale (20%) Shipped is not done. You keep AI products healthy and improving.
Monitor AI tool performance, accuracy, and usage
Respond to user feedback and iterate — fix what's broken, improve what's clunky
Build automated validation and alerting for AI outputs
Scale successful patterns to new use cases and new user groups
Document what you build so others can extend it
Standardize AI Patterns for the Team (10%) The team already uses AI individually. You make the best patterns reusable.
When you build something that works, package it: shared agents, reusable skills, prompt templates, standard workflows
Contribute to the team's AI development practices — not by mandating, but by building things others want to copy
Keep the team current on what's working and what's not in the AI tooling landscape
Basic Qualifications
3+ years of data engineering experience
Experience with data modeling, warehousing and building ETL pipelines
Experience with SQL
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.
Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company’s reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.
Our inclusive culture empowers Amazonians to deliver the best results for our customers.
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Compétences linguistiques
- English
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