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Salary: CAD 89,000 - 105,000 / annual
Airbyte is the data and action layer for AI agents, providing fast, accurate, authenticated access to business data across hundreds of sources. The company has raised $181M from leading investors and is now building production-grade agent infrastructure on an open foundation.
As a Technical Support Engineer, you will be the technical backbone for Airbyte's growing cloud and embedded integration platform. You'll combine deep technical expertise with genuine customer empathy to support customers through complex data integration challenges.
Key Responsibilities:
Customer Support & Troubleshooting: Respond to customers via email, ticketing systems, and video calls with clarity and care. Triage and prioritize issues while meeting SLA targets, leveraging AI tools to work smarter. Dig into complex issues across APIs, connectors, data pipelines, and SaaS integrations, partnering with Engineering to drive root-cause fixes. Document and reproduce customer-reported bugs with sufficient detail for quick action. Support embedded platform customers through onboarding and troubleshooting, including OAuth flows, widget tokens, scoped API tokens, and connector configuration.
API & Technical Expertise: Get hands-on with customers building and debugging integrations, helping them navigate the Airbyte API and third-party APIs with confidence. Test and validate API endpoints, review request/response payloads, and guide customers through integration best practices. Support customers with the Embedded API and Airbyte MCP, covering source creation, connector template management, and widget token authentication. Help customers building on the Airbyte Connector SDK, including YAML-based connector definitions, OpenAPI specs, and cassette-based testing workflows. Stay current on Airbyte's API surface, new connector releases, and platform updates.
Cross-Functional Collaboration: Be the voice of the customer inside Airbyte, working closely with Engineering and Product to surface issues, advocate for feature requests, and influence the roadmap. Partner with Engineering teams to relay platform-specific feedback, connector gaps, and SDK usability issues. Collaborate with Sales and Customer Success on technical conversations, onboarding, and expansion efforts.
Knowledge & Process Improvement: Create and maintain internal and external knowledge base articles, troubleshooting guides, and API documentation. Document research and troubleshooting processes to aid faster ticket resolution and team knowledge-sharing. Identify opportunities for automation and process improvements with AI. Spearhead initiatives to fill organizational or support gaps.
Requirements:
- 3+ years in technical support, data engineering, DevOps, QA, or similar role supporting developers or technical users
- Hands-on experience with RESTful APIs and GraphQL, including OAuth, pagination, webhooks, rate limiting, and error handling
- Proficiency with API testing tools like Postman or cURL
- Understanding of cloud platforms (AWS, GCP, or Azure) and data integration concepts including ELT/ETL workflows
- Strong troubleshooting instincts, clear communication with both technical and non-technical stakeholders, and a growth mindset
- Demonstrated use of AI tools to speed up troubleshooting or automate workflows (agents, MCP, prompt and context engineering)
- High tolerance for ambiguity and natural self-starter mentality
Nice to Have:
- Familiarity with Python, Java, or Kotlin and experience with CI/CD pipelines and GitHub
- Experience with container orchestration tools like Kubernetes or Docker and multi-tenant architectures
- Background supporting developer-facing or embedded/platform products in B2B SaaS
- Familiarity with OpenAPI specs, YAML configuration, and Jinja expressions
- Experience with SQL and working knowledge of databases, including CDC setups
