AI Data Engineer

What you get this onsite AI Data Engineer role in Hawthorne, CA offers a competitive salary range of USD 132,100 to 178,800 per year, comprehensive health benefits, retirement matching, and equity opportunities. You will join a collaborative team focused on AI powered analytics for Ring and Blink Customer Service, turning early prototypes into scalable production systems and owning the AI data layer that sits atop the data infrastructure.

Benefits

• Health coverage including medical, dental, vision, and prescription drugs, plus Basic Life and AD&D with optional supplemental life plans, EAP and Mental Health Support, and a Medical Advice Line
• Flexible Spending Accounts
• Adoption and Surrogacy Reimbursement
• 401(k) matching
• Paid time off
• Parental leave
• Sign-on payments
• Restricted stock units

In this role, you will help shape how AI capabilities are integrated into customer service analytics, delivering reliable and scalable data-centered AI solutions.

Responsibilities

• Develop and deploy conversational analytics agents that enable natural language queries over customer service data
• Productionize AI teammates and agents for use cases such as transcript analysis, metrics Q and A, contact summarization, and pipeline monitoring using internal platforms and cloud based frameworks
• Integrate the full stack from data sources like Redshift and S3 through the AI layer of LLMs, agents, and semantic logic to the user interface
• Own end-to-end delivery from prototype handoff to production deployment, user onboarding, and iterative improvement
• Build validation mechanisms to verify AI responses against the source of truth
• Define and maintain the semantic layer including metric definitions, business logic, and data scope
• Design guardrails for data access, in scope questions, and handling uncertainty
• Own the permission architecture for AI tools, covering user groups, access policies, and cross-account controls
• Implement confidence scoring, audit trails, and feedback loops
• Monitor AI tool performance, accuracy, and usage
• Address user feedback and iterate to fix issues and improve usability
• Develop automated validation and alerting for AI outputs
• Scale successful patterns to new use cases and additional user groups
• Document builds so others can extend and reuse them
• Package effective solutions as shared agents, reusable skills, prompt templates, and standard workflows
• Contribute to the team AI development practices by delivering tangible assets others will adopt
• Keep the team informed on what is working and what is not in the AI tooling landscape

Requirements

• Minimum of 3 years of data engineering experience
• Experience with data modeling, warehousing, and building ETL pipelines
• Proficiency in SQL

Technologies

• Redshift
• S3
• LLMs
• AWS Glue
• EMR
• Kinesis
• Firehose
• Lambda
• IAM