Perplexity AI

Member of Technical Staff (Software Engineer, Connector Platform)

San Francisco · Staff+

Sponsorship not specifiedDetected 37 days ago

PythonGoAWSKubernetesOAuthLLMsIncident Response

About the role

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.

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.
Build the connector onboarding path (schemas, fixtures, and evaluation suites) so new connectors ship with measurable quality rather than hope, and drive the eval metrics that tell us a connector actually works inside agent loops.
Partner with product and AI teams to define clear connector interfaces and integration patterns so new agent capabilities can reliably build on the shared platform.
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.

Strong proficiency in at least one backend language such as Python, Go, or Rust, and the ability to work effectively in a multi-language environment.
Hands-on experience with modern infrastructure (for example AWS, Kubernetes, and related cloud technologies).
Comfort working in security-sensitive areas (auth, authorization, credential isolation) and making pragmatic trade-offs between safety, simplicity, and velocity.
Experience designing and building backend systems that run in production (typically 4+ years for mid-level, more for senior and staff).
Strong system design skills, with a track record of building efficient, reliable, and scalable architectures, ideally including API integration, gateway, or platform-style systems with many heterogeneous downstreams.
Depth in at least one of: OAuth and authorization protocols, API/connector or MCP-server development, schema and semantic modeling, or building tooling and evaluation for LLM-based agents.
Collaborative mindset and eagerness to solve hard, ambiguous problems alongside other experienced engineers.
If you're excited about this role, we encourage you to apply even if your experience doesn't match every qualification listed above.

Models are commoditizing; grounded, actionable, permissioned access to a customer's real systems is not.

This listing is sourced directly from Perplexity AI's careers page and normalized into a canonical job model.