SlipstreamJobs tracks this role from the company's public career site. Apply directly on the employer's site.
Perplexity's Enterprise Knowledge Platform team is building the data and action layer that connects AI agents to enterprise systems where work actually happens. This is a product and platform engineering role with end-to-end ownership spanning connector infrastructure, semantic modeling, and customer-facing marketplace experiences.
You will own the connector runtime that registers, hosts, and executes native connectors, MCP servers, and CLI-backed tools through a unified agent-facing interface. You'll build the semantic and knowledge layer—including tool schemas, capability metadata, organizational terminology, and permission-aware context—that makes enterprise data reusable across connectors while preserving provenance and access controls.
Key responsibilities include designing discovery and recommendation systems that help agents find relevant tools and help users select integrations; building the marketplace and activation experience end-to-end (browsing, recommendations, installation, configuration, admin enablement); ensuring reliable connector execution with structured results, retries, idempotency, pagination, and rate-limit handling; owning reliability targets, production monitoring, and incident response; implementing authentication, credential isolation, and permission enforcement in partnership with Trust, Security, and Backend Platform teams; and building the onboarding and publishing path for internal and external partners.
This role bridges backend infrastructure and customer-facing product, requiring you to translate complex integration requirements into clear APIs, developer tools, and intuitive workflows. You'll work across AI Research and Enterprise teams to turn fragmented systems into reliable, permission-aware capabilities that agents can use to complete real work.
Qualifications:
- 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, or MCP servers (including authentication and authorization); schema design, semantic modeling, or knowledge systems; search, ranking, recommendation, or tool discovery systems; or marketplaces, developer platforms, or enterprise onboarding and activation experiences
- Ability to work across backend infrastructure and customer-facing product experiences
- Sound technical judgment in security-sensitive, distributed systems
- Track record of leading ambiguous, cross-team initiatives from architecture through adoption, setting technical direction for shared platforms, and raising engineering quality through mentorship
