← Back to results

Member of Technical Staff (Software Engineer, Enterprise Knowledge Platform)

Join the Connector Platform team to design and implement a unified data layer for Perplexity's agents.

Location
San Francisco
Compensation
Not disclosed
Level
mid
Type
full time

Posted by employer 4 months ago

First seen on Joblaze 2 months ago

Last verified on the company career page 1 day ago

Apply at Perplexity AI → Save job Scanned from perplexity.ai

Skills & Technologies

Requirements

Experience
4+ years

Not disclosed in this posting: compensation, work arrangement, visa sponsorship.

Joblaze summary

In this role, the engineer will design and implement the connector runtime, ensuring that various integrations function seamlessly within Perplexity AI's platform. Key skills include backend system design, proficiency in languages like Python or Go, and experience with modern infrastructure tools such as AWS and Kubernetes. This position is ideal for mid to senior-level professionals with a strong background in API integration and a collaborative approach to solving complex problems. The team focuses on creating a reliable data layer that enhances the capabilities of AI agents.

Joblaze insights

  • Listed about 2 months ago — first seen on Joblaze September 3, 2026. Last confirmed on Perplexity AI's careers page November 6, 2026.
  • Python appears in 36.2% of 531 comparable mid backend roles; Rust appears in 15.3% of 531 comparable mid backend roles.

Quick facts

How much experience is required?
At least 4 years of relevant experience for this Member of Technical Staff (Software Engineer, Enterprise Knowledge Platform) role.
What's the tech stack?
Joblaze extracted these technologies from the posting: AWS, Go, Kubernetes, Python, Rust.
What seniority level is this role?
Perplexity AI targets mid-level candidates for this position.
Is this full-time or contract?
Full-time for this Member of Technical Staff (Software Engineer, Enterprise Knowledge Platform) role at Perplexity AI.

From the original posting

About the Role

The Enterprise Knowledge Platform team builds the data and action layer that connects Perplexity's agents to the systems where enterprise work happens. Useful agents need more than access to APIs: they need to discover the right tools, understand an organization's data and terminology, and act reliably within its permissions. This team brings native connectors, MCP servers, and CLI-backed tools into a consistent platform, and builds the marketplace through which customers adopt integrations and partners extend the ecosystem.

This is a product and platform engineering role with end-to-end ownership, from designing connector infrastructure and semantic models to shipping the experiences customers use to discover, connect, and activate integrations. You'll build the runtime that executes tool calls, the knowledge layer that makes enterprise context reusable across connectors, and the developer and marketplace foundations that help the ecosystem grow. Working with AI Research and Enterprise teams, you'll turn fragmented systems into reliable, permission-aware capabilities that agents can use to complete real work. The impact is direct: every improvement helps customers put their existing software and knowledge to work through Perplexity.

Key Responsibilities

  • Own the connector runtime that registers, hosts, and executes native connectors, hosted MCP servers, and CLI-backed tools through a consistent agent-facing interface.

  • Build the semantic and knowledge layer, including tool and entity schemas, capability metadata, relationships, organization-specific terminology, and reusable corrections, while preserving provenance and source-system permissions.

  • Design discovery, search, and recommendation systems that help agents find relevant tools and context and help users and organizations choose integrations that fit their work.

  • Build the marketplace and activation experience end to end, from browsing and recommendations to installation, configuration, admin enablement, and ongoing adoption.

  • Make connector execution reliable and observable, with structured results, retries, idempotency, pagination, rate-limit handling, and recovery from partial failures. Own reliability targets, production monitoring, and incident response.

  • Implement connector authentication, credential isolation, and permission enforcement, partnering with Trust & Governance, Security, and Backend Platform on shared policies and tenant boundaries.

  • Build the onboarding and publishing path for internal teams and external partners, including schemas, test fixtures, validation, review, and versioning.

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 the following:

    • Connector runtimes, API platforms, or MCP servers, including authentication and authorization.

    • Schema design, semantic modeling, or knowledge systems that capture relationships and organizational context.

    • Search, ranking, recommendation, or tool discovery systems.

    • Marketplaces, developer platforms, or enterprise onboarding and activation experiences.

  • 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.

  • A track record of leading ambiguous, cross-team initiatives from architecture through adoption, setting technical direction for shared platforms, and raising engineering quality through mentorship.

If you're excited about this role, we encourage you to apply even if you don't meet every qualification. We value demonstrated impact, deep ownership, and the initiative to turn ambiguity into results.