Company
Technology
MemberofTechnicalStaff(SoftwareEngineer,ConnectorPlatform)
Neural analysis suggests this role is
optimal for Senior candidates.
“Member of Technical Staff (Software Engineer, Connector Platform). Skills: Connector platform, Data layer, Knowledge layer, Agent integration. Own design and implementation of connector runtime. Register connectors”
Industry & Context.
Ambiguous problems
What They're Looking For.
Must Have
4+ years backend systems experience, System design skills, Backend systems that run in production, API integration experience, Gateway experience, Platform-style systems experience, Proficiency in Python, Proficiency in Go, Proficiency in Rust, Work effectively in multi-language environment, Hands-on experience with modern infrastructure, Experience with AWS, Experience with Kubernetes, Experience with related cloud technologies, Depth in OAuth, Depth in authorization protocols, Depth in API/connector development, Depth in MCP-server development, Depth in schema modeling, Depth in semantic modeling, Depth in building tooling for LLM agents, Depth in building evaluation for LLM agents, Comfort working in security-sensitive areas, Pragmatic trade-offs between safety, simplicity, and velocity
Nice to Have
Experience designing and building backend systems (typically 4+ years for mid-level, more for senior and staff), Experience with heterogeneous downstreams, Experience with cloud-native architecture, Experience with distributed systems
What You'll Do.
Own design and implementation of connector runtime
Execute built-in connectors
Execute hosted MCP servers
Execute CLI-backed tools
Extend semantic layer
Capture organization-specific corrections
Apply organization-specific corrections
Capture account-specific corrections
Apply account-specific corrections
Design tool-discovery surfaces
Design tool-selection surfaces
Optimize for model accuracy
Optimize for context efficiency
Make agent loops robust
Define authentication patterns
Define authorization patterns
Define credential-isolation patterns
Build connector onboarding path
Ship new connectors with measurable quality
Set technical bar for reliability
Set technical bar for operability
Monitor incident response
Partner with product teams
Partner with AI teams
Define clear connector interfaces
Define integration patterns
How You'll Work.
Team & Collaboration
Partnering with Security; Partnering with Backend Platform; Partner with product teams; Partner with AI teams
Full Job Description
ABOUT THE ROLE The Connector Platform team builds the data layer that lets Perplexity's agents reach into the world's software. This team owns the systems that turn hundreds of heterogeneous integrations (native, MCP, CLI, first-party, and third-party APIs) into one unified, reliable, well-typed surface that agents can call with confidence. The connector platform is the core layer that forms the knowledge layer for Computer: it is how the agent discovers what tools exist, understands what each one means, decides which to call, and grounds its reasoning in real, permissioned, up-to-date enterprise data. We maintain a knowledge layer above connectors that pushes and pulls context into them, rather than letting each connector hoard org knowledge on its own, making Computer the source of truth for institutional knowledge. Models are commoditizing; grounded, actionable, permissioned access to a customer's real systems is not. When this layer is fast, accurate, and semantically rich, every agent built on top of it gets smarter; when it is weak, no amount of model quality compensates. KEY RESPONSIBILITIES - Own the design and implementation of the connector runtime, the system that registers, hosts, and executes built-in connectors, hosted MCP servers, and CLI-backed tools behind a single agent-facing interface. - Build and extend the semantic layer: tool and entity schemas, capability metadata, relationship modeling, and the mechanisms for capturing and applying organization- and account-specific corrections and knowledge. - Design the tool-discovery and tool-selection surfaces that agents use to find the right connector and call it correctly, optimizing for both model accuracy and context efficiency. - Make agent loops robust: structured results, partial-failure and retry semantics, idempotency, pagination, rate-limit handling, and observability into every tool call an agent makes. - Define authentication, authorization, and credential-isolation patterns for connectors (
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