Level

Perplexity

Software Engineer, Enterprise Knowledge Platform

Perplexity is hiring a Software Engineer, Enterprise Knowledge Platform in San Francisco, United States. It pays $220k-$405k a year and Level rates it ; you can apply on Perplexity.

Level's read on this job

  • Level rates this software engineer role Works on AI ●●●○: the daily work is on AI products, without building the model.
  • Pay on this posting starts 31% higher than the typical software engineer posting on Level.
  • The posting mentions MCP, Cli and AI research among its tools and skills.
  • Perplexity has 132 other open roles on Level.
  • Posted in the last few days.

AI in this role

Build the enterprise knowledge platform, connectors, and runtime that connect AI agents to internal systems and tools.

mcpcli
ai-researchbackend-engineeringdistributed-systemsapi-integrationauthentication

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.

How we rate this

Software Engineer, Enterprise Knowledge Platform at Perplexity rates 75 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.

Classification

Works on AI. The daily work is on AI products, without building the model.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

AI ResearchBackend EngineeringDistributed SystemsAPI IntegrationAuthenticationMCPCli

Also common in software engineer jobs at this level

Pay

This job starts at
$220k
Typical software engineer job
$168k

This posting starts 31% above the typical software engineer job. See software engineer jobs

Questions you could be asked

  1. Tell me about a research question you investigated. What did you find?
  2. Tell me about a project where backend engineering was part of your work. What did you do?
  3. Tell me about a project where distributed systems was part of your work. What did you do?
  4. Tell me about a project where api integration was part of your work. What did you do?
  5. Tell me about a project where authentication was part of your work. What did you do?

Adapt your resume

  • List these exact terms on your resume: AI Research, Backend Engineering, Distributed Systems, API Integration, and Authentication. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
  • Show where AI is part of your daily process, not a one-off project. This role expects it to be a running habit.

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