Member of Technical Staff (Software Engineer, Connector Platform)

Perplexity; Palo Alto (CA); On-site; USD 220,000 - 405,000; Full time

Job summary

Perplexity is seeking a backend-focused engineer to drive the Connector Platform’s runtime and connectors, enabling agents to reach into enterprise software with confidence.

You will extend the semantic layer, design tool discovery and selection mechanisms, and ensure robust agent loops with strong observability and security in mind. This role emphasizes collaboration with product and AI teams in a fast-paced environment.

Qualifications

• Experience designing and building production backend systems (4+ years for mid-level, more for senior/staff).
• Strong system design skills with scalable architectures and multi-downstream integration experience.
• Proficiency in Python, Go, or Rust and ability to work in multi-language environments.
• Hands-on experience with modern infrastructure (AWS, Kubernetes, and related cloud tech).
• Depth in OAuth, authorization protocols, API/connector or MCP-server development, schema/semantic modeling, or LLAm-based tooling/evaluation.
• Comfort working in security-sensitive areas and balancing safety, simplicity, and velocity.
• Collaborative mindset with willingness to tackle hard, ambiguous problems.

Responsibilities

• Own the design and implementation of the connector runtime and hosted tools behind a single agent-facing interface.
• Extend the semantic layer: tool schemas, capability metadata, and knowledge corrections.
• Design tool-discovery and tool-selection surfaces for accurate model calls and context efficiency.
• Ensure agent loops are robust with structured results, partial failures, retries, and observability.
• Define authentication, authorization, and credential isolation patterns in collaboration with Security and Backend Platform.
• Build onboarding paths with schemas and evaluation suites to ship quality connectors.
• Set SLAs, observability, error-rate monitoring, and incident response for a high-fan-out surface.
• Partner with product and AI teams to define connector interfaces and integration patterns.

Skills

Backend design

System design

Python/Go/Rust

Cloud infra (AWS/Kubernetes)

OAuth/authorization

Security-conscious

Collaborative problem-solving

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.

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 (OAuth flows, BYOK, per-org credential boundaries), partnering with Security and Backend Platform on defense-in-depth.
• 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.
• Set the technical bar for connector reliability and operability: SLAs, observability, error-rate monitoring, and incident response for an always-on, high-fan-out integration surface.
• 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.

Qualifications

• 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.
• 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).
• 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.
• Comfort working in security-sensitive areas (auth, authorization, credential isolation) and making pragmatic trade-offs between safety, simplicity, and velocity.
• Collaborative mindset and eagerness to solve hard, ambiguous problems alongside other experienced engineers.

Compensation Range: $220K - $405K