Senior Architect AI-Driven Data Intelligence

Yahoo Holdings Inc. in; Champaign (IL); Hybrid; USD 144,000 - 299,000; Full time

Benefits offered by this job

Healthcare

401(k) plan

Backup childcare

Education stipends

Job summary

Yahoo Holdings Inc. is seeking a Principal Engineer – Data Intelligence to lead architecture and development of AI-powered data platforms at Yahoo scale.

You will focus on retrieval-augmented data workflows, governance signals and enterprise metadata integration, shaping reusable platform capabilities across engineering and analytics teams. The role emphasizes rigorous correctness, reliability, security, and operational safety while enabling AI-assisted development and automation.

Qualifications

• 10+ years building distributed systems and large-scale data platforms.
• Deep Python expertise and strong software engineering.
• Production experience with batch and streaming processing (Kafka, or equivalent).
• Shipped and operated RAG applications in production; focus on AI safety.

Responsibilities

• Define technical vision and architecture for Yahoo's AI-powered data intelligence platform.
• Architect petabyte-scale batch and streaming systems with Beam, Dataflow, Spark, and Kafka.
• Build production RAG and multi-agent systems: semantic metadata integration, agent orchestration.
• Establish evaluation frameworks for retrieval quality, agent accuracy, hallucination rate, safety.
• Use AI development tools to accelerate design and validate AI-generated code and agent plans.
• Drive adoption of RAG and agentic patterns across engineers.
• Partner with product, governance, infrastructure, and priority teams.

Skills

Distributed systems

Python

Data engineering

Leadership

Education

Bachelor’s degree in CS/AI/ML/Engineering/Math

Tools

Kafka

Beam

Dataflow

Spark

BigQuery

Job description

Yahoo Holdings Inc. is seeking a Principal Engineer – Data Intelligence to lead architecture and development of AI-powered data platforms at Yahoo scale.

You will focus on retrieval-augmented data workflows, governance signals and enterprise metadata integration, shaping reusable platform capabilities across engineering and analytics teams. The role emphasizes rigorous correctness, reliability, security, and operational safety while enabling AI-assisted development and automation.