About the role
Airbyte is the data and action layer for AI agents. We give agents fast, accurate, authenticated access to business data across hundreds of sources, so they can discover the entities that matter, reason over real-time context, and take action in the systems they read from, not just observe them. We started as the open-source standard for data movement and proved the economics of data integration at scale: hundreds of connectors, thousands of companies, and, since 2020, have raised $181M from leading investors including Benchmark, Accel, Altimeter, Coatue, and Y Combinator. As our CEO Michel Tricot puts it, "the last ten years were all about structured data. The future is all about context." We're now building that context infrastructure for production-grade agents on the same open foundation, as agents become the primary consumers of enterprise data. Our mission is unchanged: make data available and actionable to everyone, everywhere. That everyone now includes AI agents. Engineering Hiring Sprint: We're growing our engineering team and are accelerating hiring through a focused Engineering Hiring Sprint. Rather than stretching interviews over several weeks, we're bringing exceptional candidates through an expedited process and making hiring decisions quickly. Interview process: Apply Technical Take-Home (Java or Python) Hiring Manager Interview In-Person Onsite (the week of July 20) Hiring decision by the end of the week We're hiring across multiple engineering teams, including: ⚙️ Platform Engineers 🗄️ Database Engineers ☁️ Site Reliability Engineers 🔌 Extensibility API Engineers 🤖 AI Agents Engineers 👤 Engineering Managers If you enjoy solving complex technical problems, moving quickly, embracing AI, and taking ownership of your work, we'd love to meet you.
The Role: At Airbyte, connectors are the product. Every sync, every AI workflow, and every customer use case depends on our ability to reliably integrate with APIs, databases, filesystems, and SaaS platforms at massive scale. We’re looking for an Integrations Engineer to help build the future of AI-assisted integrations at Airbyte. This role spans both Airbyte Data Replication and Airbyte Agents, our AI-native platform that gives agents reliable, real-time access to business data through managed connectors, secure credential handling, a searchable Context Store, and agent-facing interfaces including APIs, MCP, SDKs, CLI tooling, and the web application. You’ll work primarily in Python across our CDKs, Connector Builder ecosystem, automation frameworks, rollout systems, and AI-driven operational tooling. This is a highly autonomous role for an engineer who thrives in ambiguous environments, exercises strong technical judgment, and wants to shape how AI changes software development and operational reliability. You’ll help drive Airbyte toward a future where connectors increasingly maintain themselves through intelligent automation, adaptive rollouts, and AI-assisted remediation. What You’ll Do: Build and evolve the Python systems that power integrations across both Airbyte Data Replication and Airbyte Agents. 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. Build systems that use AI to detect, diagnose, and remediate connector failures with minimal human intervention. Design tooling and abstractions that enable Airbyte engineers to build, roll out, and monitor integrations faster and more reliably. Drive initiatives focused on self-healing infrastructure, intelligent retries, automated compatibility fixes, and operational resilience. Partner closely with Customer Engineering and Support teams to identify recurring operational issues and eliminate them systematically through automation and platform improvements. Lead technically ambiguous projects from exploration through production rollout while balancing speed, reliability, and long-term maintainability. Mentor engineers, raise technical standards, and help shape engineering direction across the integrations ecosystem. What You’ll Need: 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. Strong communication skills and the ability to collaborate effectively across engineering, product, support, and customer-facing teams. Experience mentoring engineers and influencing technical direction beyond your immediate team. A strong bias toward shipping, iteration, experimentation, and continuous improvement. Passion for developer experience and building tools that make other engineers dramatically more effective. Belief in our values and a willingness to own outcomes end-to-end.
