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The Enterprise Knowledge Platform team at Perplexity AI builds the data and action layer connecting AI agents to enterprise systems. This role owns end-to-end product and platform engineering, from connector infrastructure and semantic models to customer-facing integration experiences.
You will build the runtime that registers, hosts, and executes native connectors, MCP servers, and CLI-backed tools through a consistent agent interface. You'll design and implement the semantic and knowledge layer—including tool schemas, capability metadata, organizational terminology, and permission-aware context—while preserving provenance and source-system permissions.
Key responsibilities include designing discovery and recommendation systems that help agents find relevant tools and users select integrations; building the marketplace and activation experience end-to-end (browsing, recommendations, installation, configuration, admin enablement, adoption); ensuring connector execution reliability with structured results, retries, idempotency, pagination, rate-limit handling, and failure recovery; implementing authentication, credential isolation, and permission enforcement in partnership with Trust, Security, and Backend Platform teams; and building onboarding and publishing paths for internal and external partners.
You'll work across backend infrastructure and customer-facing product, translating complex integration requirements into clear APIs and intuitive workflows. The impact is direct: every improvement helps customers activate their existing software and knowledge through Perplexity's agents.
REQUIREMENTS:
- 4+ years of software engineering experience with a track record of owning complex backend systems from design through production operation
- Strong system design skills, including building reliable, scalable platforms that integrate heterogeneous APIs and services with clear security and isolation boundaries
- Strong proficiency in a backend language such as Python, Go, or Rust, and hands-on experience with cloud infrastructure such as AWS and Kubernetes
- Deep expertise in at least one of: connector runtimes/API platforms/MCP servers (including authentication and authorization); schema design/semantic modeling/knowledge systems; search/ranking/recommendation/tool discovery systems; or marketplaces/developer platforms/enterprise onboarding
- Ability to work across backend infrastructure and customer-facing product experiences, translating complex integration requirements into clear APIs, developer tools, and intuitive workflows
- Sound technical judgment in security-sensitive, distributed systems, balancing credential isolation, permission correctness, and failure behavior with performance, usability, and delivery speed
- Track record of leading ambiguous, cross-team initiatives from architecture through adoption, setting technical direction for shared platforms, and raising engineering quality through mentorship
About Perplexity AI
AI / Data / Infrastructure — AI answer engine and search product for consumers and enterprises.
