Integrations Engineer

Build and maintain production-grade data integrations and ingestion pipelines connecting enterprise systems to Hebbia's AI platform. Requires 2-5 years experience with Python, backend services, and API integrations in a high-ownership, on-call production environment.

About the job

Responsibilities

Build connectors and ingestion pipelines that bring enterprise data into Hebbia's AI platform, from Snowflake warehouses and SharePoint libraries to live pricing feeds, high-velocity news data, and proprietary customer systems
Design and operate pipelines that handle scale, failures, and edge cases gracefully
Debug issues across APIs, auth systems, and data formats, often under real-time customer pressure
Own reliability end-to-end: monitoring, alerting, on-call, and incident response
Improve internal tooling and observability to make systems more robust and easier to operate
Partner with product and customer teams to scope, prioritize, and ship the integrations that unlock Hebbia's highest-value use cases
Design and ship agents that sit on top of the ingestion layer, making enterprise data accessible and actionable across all of Hebbia's product surfaces

Requirements

2–5 years of software engineering experience, ideally at a startup or high-growth technology company
Strong proficiency in Python, with experience building backend services and APIs
Direct experience building or maintaining integrations with third-party APIs—you understand OAuth flows, webhook patterns, rate limiting, pagination, and the ways APIs break in practice
Comfortable with cloud infrastructure (AWS preferred) and tools like Kafka, PostgreSQL, Redis, or ElasticSearch
Operational mindset: you take ownership of systems in production, not just in a PR. You are comfortable with on-call and treat reliability as a first-class concern
Strong debugging instincts—you can trace a data issue from a customer report through logs, API responses, and queue state to root cause
Clear communicator who can explain technical issues to non-technical stakeholders when a customer’s integration is down
Autonomous and self-directed

Nice-to-Haves

Experience with enterprise data platforms (Snowflake, SharePoint, Salesforce) from the integration side
Familiarity with document processing pipelines or content extraction systems
Experience building agentic systems or LLM-enabled products
Frequent user of AI tools in your development workflow (Cursor, Claude Code, etc.)