AI Data Engineer – United States

last updated November 19, 2025 19:13 UTC

AHEAD

HQ: Hybrid

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Architect, build, and operate real-time/batch ETL pipelines, agentic orchestration flows, and AI/ML endpoints for autonomous, multi-agent production systems. Contribute actively to team processes, documentation, and operational quality.
Responsibilities

    • Build event-driven data workflows (Snowflake, S3, Kafka, EventBridge, Celery, AWS Batch), integrate with FactSet, Sharepoint, Proxy connectors, and expose agentic features (LangChain, LangGraph, LlamaIndex, Pinecone).
    • Develop, maintain, and monitor vector database (Pinecone) pipelines, LLM and ML endpoints, ensuring agent memory/state is managed for retrieval-augmented pipelines.
    • Automate schema/version change management, event contract validation, lineage tracking, and observability.
    • Write, run, and document QA/test coverage for ETL, agentic triggers, and GenAI model events, with incident and postmortem participation.
    • Collaborate in agile ceremonies: propose improvements, troubleshoot delivery bottlenecks, and share technical knowledge via docs and training sessions.
    • Implement and monitor security, compliance, and resiliency standards at all stages of the data/model workflows.
    • Help onboard new team members; mentor engineers in agentic and event-driven data engineering best practices.
Qualifications

    • Event-driven ETL/data pipeline experience (Kafka, EventBridge, Snowflake, S3, Python/Celery), plus direct work with LangChain/LangGraph/LlamaIndex/Pinecone multi-agent orchestration.
    • QA, documentation, monitoring, and collaborative agile process skills.
    • Experience with cross-cloud, multi-source integration and incident resolution.
$170,000 – $200,000 a year
Apply info ->

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