26 open roles · R&D
Senior Backend AI Engineer
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Where you can work
On-site
Cleveland, Ohio, United States
View location wording from the posting
- Cleveland, Ohio
- Cleveland, OH
Employer description
Sr. Backend AI Engineer
Location: Cleveland, OH
Role Overview Move beyond traditional ETL. At BrightEdge, we are rebuilding our core data infrastructure into an AI-augmented processing engine. We’re looking for a Senior Backend Engineer to architect "intelligent" systems that don't just move data, but understand it. You will build self-healing pipelines and agentic workflows that allow our platform to autonomously adapt to complex, shifting data landscapes.
What You’ll Do
Architect Agentic Pipelines: Build Python-based backend systems that utilize LLMs and AI agents to automate the discovery, parsing, and mapping of unstructured data.
Build Self-Healing Infrastructure: Develop autonomous reliability layers that diagnose upstream failures, adapt to API schema changes, and perform real-time data validation without manual intervention.
Optimize High-Velocity Analytics: Design and manage low-latency data flows into ClickHouse and BigQuery, ensuring our AI-driven insights are backed by high-performance OLAP architecture.
Scale Intelligent Connectors: Create robust integrations (APIs, Streaming, S3) that leverage AI to handle diverse, non-standardized data sources at massive scale.
Engineering Leadership: Drive best practices in AI-assisted testing and observability, mentoring the team on the intersection of traditional backend stability and modern AI capabilities.
What You Bring
5+ years experience with Bachelor's degree in Computer science, Software Engineering
Python & AI Mastery: Deep expertise in production-level Python. You’ve successfully integrated AI models/LLMs into backend services or data workflows.
OLAP Power User: Proven experience with ClickHouse, BigQuery, or Snowflake, specifically in schema optimization and materialized views for large-scale datasets.
Distributed Systems Expertise: Strong background in cloud environments (GCP/AWS) and real-time streaming tools like Kafka, Flink, or Spark.
Adaptive Mindset: You don't just build to a spec; you build systems that anticipate and recover from environment changes autonomously.
Product Ownership:A track record of leading high-impact initiatives and a desire to own the "brain" of a global data platform
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