Senior Solutions Architect

What You’ll Do

• Technical Implementation: Lead and execute impactful customer technical projects, including the implementation and deployment of Airbyte solutions, while ensuring alignment with client requirements and industry best practices.
  • Guide customers throughout their customer journey by leveraging your technical expertise and stepping in with hands-on support when needed.
    • Design and implement AI-powered data pipeline architectures using frameworks such as LangChain, LlamaIndex, or Haystack to enable intelligent data workflows for enterprise customers.
  • Deep understanding of database technologies, including SQL, CDC (Change Data Capture), database replication, and data synchronization concepts, with the ability to troubleshoot complex data movement issues.
    • Strong knowledge of REST APIs, including HTTP methods, authentication (OAuth, API keys, JWT), webhooks, and JSON, with the ability to troubleshoot complex integration issues.
  • Advise customers on integrating LLM-based tooling into their existing data infrastructure alongside Airbyte connectors.
• Client Engagement: Work directly with clients’ technical teams to understand their needs and tailor solutions accordingly. Manage technical success by collaborating with Airbyte’s technical support, Product, and Engineering teams to address issues and deliver new features. Help clients evaluate and adopt AI agent frameworks to build autonomous data agents that leverage Airbyte as a data source.
• Cross-Department Collaboration: Collaborate with Sales to identify and drive potential growth opportunities with customers. Act as the internal source of truth for customer technical requirements, expectations, and needed functionalities. Partner with Product and Engineering teams to surface customer needs, influencing the roadmap.
• Advocacy and Evangelism: Demonstrate the use and best practices of Airbyte’s offering to clients and at industry events. Serve as a brand ambassador promoting the organization’s mission and fostering relationships with key stakeholders. Evangelize best practices for building AI-ready data stacks.

What You’ll Need

• 6+ years of experience in a customer facing technical role, such as resident solutions architect, professional services engineer, or consulting role.
• 2+ years of experience in a startup environment, ideally in modern data infrastructure, including cloud applications, databases, ELT tools, data warehouses or related fields (startup implementation experience is a bonus).
• Hands-on experience with one or more AI frameworks.
• Exposure to AI agent frameworks and prompt engineering best practices is a strong plus.
• Proven track record of supporting products that directly impact business productivity.
• Exceptional customer orientation with a focus on delivering seamless onboarding and ongoing technical success.
• Strong interpersonal and presentation skills.