Build and scale connectors to a wide variety of SaaS and on-prem systems (Google Workspace, Microsoft 365, Slack, Salesforce, Jira, ServiceNow, GitHub, etc.)
Handle full syncs, low-latency incremental updates via webhooks/APIs, rate-limiting, and complex authentication flows
Build advanced capabilities in datasources like actions, live-fetch, and query language support
Transform raw, unstructured enterprise content into rich, structured, permission-aware representations optimized for search and LLM reasoning
Design document schemas and enrichment pipelines (entity extraction, access-graph propagation, redactions, etc.)
Expand the capabilities of AI products through deep integrations that allow us to automate tasks, perform complex queries grounded in enterprise data, and enhance our indexed corpus with live data
Own end-to-end correctness, freshness, and performance for petabyte-scale data flows
Solve hard problems in ordering, idempotency, exactly-once processing, backpressure, and retries across distributed queues, workers, and storage
Preserve fine-grained ACLs, deletions, and sensitivity constraints so AI answers are always grounded in what users are actually allowed to see
Partner closely with Search Serving, Product, Platforms, and Security teams to define how enterprise context is exposed to LLMs and agents
Continuously improve observability, alerting, and automation to onboard larger customers and more data sources with confidence