Senior Integrations Engineer (api Sources & Automation)

Airbyte Airbyte · Data AI · San Francisco, CA · Engineering

Senior Integrations Engineer at Airbyte, focusing on building AI-native data infrastructure for AI agents. The role involves developing Python systems for data replication and agent platforms, including AI-driven failure detection and remediation, and tooling for faster integration development. It emphasizes autonomous work, technical judgment, and shaping the future of AI in software development and operational reliability.

What you'd actually do

  1. Build and evolve the Python systems that power integrations across both Airbyte Data Replication and Airbyte Agents.
  2. Work on integrations that power both traditional data movement workflows and AI agent use cases, including searchable context, action execution, and real-time business data access.
  3. Build systems that use AI to detect, diagnose, and remediate connector failures with minimal human intervention.
  4. Design tooling and abstractions that enable Airbyte engineers to build, roll out, and monitor integrations faster and more reliably.
  5. Drive initiatives focused on self-healing infrastructure, intelligent retries, automated compatibility fixes, and operational resilience.

Skills

Required

  • Python
  • backend systems
  • developer tooling
  • extensible frameworks
  • APIs
  • automation systems
  • AI/LLM APIs
  • distributed systems
  • debugging
  • mentoring engineers

Nice to have

  • data integration systems
  • ETL/ELT pipelines
  • APIs
  • connector frameworks
  • Airbyte CDKs
  • Connector Builder
  • agent tooling
  • open source
  • rollout strategies
  • progressive deployments
  • automated remediation systems
  • large-scale API ecosystems

What the JD emphasized

  • 5+ years professional experience building backend systems and developer tooling in Python.
  • Experience designing extensible frameworks, APIs, automation systems, or platforms used by other engineers.
  • Experience leveraging AI or LLM APIs in engineering workflows, developer tooling, operational systems, or product experiences.
  • Ability to independently drive large or ambiguous technical initiatives and make strong tradeoff decisions with business context in mind.
  • Strong systems thinking and debugging skills across complex distributed or integration-heavy environments.
  • Experience improving engineering velocity and operational reliability through automation and platform investments.
  • Experience mentoring engineers and influencing technical direction beyond your immediate team.

Other signals

  • AI agents
  • data integration
  • automation