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Senior Software Engineer, Integrations (Databases)

Airbyte
CompanyAirbyte
CategoryEngineering
LocationSan Francisco
RemoteHybrid
EmploymentNot stated
LevelSenior
SalaryUSD 196k–255k
Posted29 Jun 2026
Last verified31 Jul 2026
SourceEmployer career page (ashby)
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Description
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. THE ROLE: At Airbyte, we're building the future of integration engineering. Our team owns the platform that powers hundreds of database and application connectors—but we don't believe scaling integrations should require scaling engineering effort. Instead, we're building an AI-powered Integration Factory that automates the lifecycle of our connectors: generating code, managing dependency updates, diagnosing production issues, proposing fixes, and continuously improving reliability. As a Senior Software Engineer on this team, you'll sit at the intersection of databases, distributed systems, AI, and developer productivity. You'll help build both the connectors themselves and the intelligent systems that create, maintain, and operate them. This is a role for engineers who love databases, enjoy building high-leverage tooling, and are excited to partner with AI rather than compete with it. You'll spend as much time improving the engineering system as you do improving the software it produces. You'll also participate in our on-call rotation, helping investigate production issues and evolving the automation that prevents similar incidents from happening again.   WHAT YOU’LL DO: - Build and evolve Airbyte's AI-powered Integration Factory. - Design intelligent systems that generate, validate, repair, and maintain connectors automatically. - Develop shared tooling, frameworks, GitHub Actions, scheduled workflows, and internal developer platforms used across hundreds of integrations. - Build highly reliable database connectors with deep support for database-specific capabilities including Change Data Capture (CDC), replication logs, query optimization, and schema evolution. - Improve connector reliability by building systems that automatically detect, diagnose, and remediate production issues. - Build infrastructure that manages dependency updates, compatibility testing, release automation, and connector health. - Contribute to Airbyte's growing AI Skills repository and help establish patterns for AI-assisted software development. - Drive step-function improvements in engineering velocity through automation and reusable tooling. - Participate in an on-call rotation, responding to production issues while continually improving the systems that reduce operational burden. - Collaborate across engineering to improve internal developer experience and platform capabilities. - Mentor engineers and raise the engineering bar through thoughtful design reviews, documentation, and technical leadership.   WHAT YOU’LL NEED: - 7+ years of software engineering experience building production systems. - Strong experience with relational databases such as PostgreSQL, MySQL, SQL Server, Oracle, MongoDB, Bigquery, Databricks, S3 or similar. - Deep understanding of SQL, query optimization, and database internals. - Demonstrated experience with AI-assisted software development, including using LLMs in the engineering workflow,
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