Perplexity AI

Member of Technical Staff (Software Engineer, Agentic Enterprise)

Perplexity AI2 weeks ago
Location

San Francisco

Type

Full Time

Salary

USD 220,000 – 405,000

Level

Senior

Role

Backend Engineer

Posted

Jul 9, 2026

Full TimeSenior

The role

Summary

Join Perplexity AI's Enterprise Adoption team as a Member of Technical Staff to architect AI agent systems that transform how organizations work. This role requires 4+ years of software engineering experience with deep expertise in modern AI agent frameworks (agents, connectors, context engineering, evals), Python proficiency, and strong product judgment to deliver enterprise-grade agentic solutions that integrate seamlessly with business operations.

What you'll do

Architect and Build Core Agent Systems: Design and implement foundational systems that enable Perplexity Computer to function as a transformative multiplier for enterprise and internal teams. Build the infrastructure that connects AI agents to business processes across recruiting, finance, legal, operations, support, and go-to-market functions, ensuring reliability and scalability at the enterprise level.
Engineer Agent Connectors and Skills Infrastructure: Develop connectors, custom skills, and evaluation infrastructure that make knowledge stores, business systems, and human-orchestrated processes legible to AI agents. Implement MCP servers, context engineering frameworks, and integration patterns that allow agents to operate effectively across diverse business domains and technical architectures.
Drive Product-Led Innovation from Internal Adoption: Partner with internal teams to identify highest-potential opportunities for agentic automation, translating friction points and successes into core product and platform improvements. Close feedback loops between real-world agent usage and product development, ensuring Computer evolves based on authentic enterprise working patterns.
Collaborate Across Disciplines on Enterprise Solutions: Work cross-functionally with Product Managers, Design, Data Science, Sales Engineers, and enterprise customers to turn process requirements into simple, reliable product experiences. Build deep empathy for non-technical stakeholders' workflows and translate their needs into technically sound agent-driven solutions.
Evaluate and Optimize Agent Performance: Design and implement evaluation frameworks that assess agent capabilities, reliability, and business impact. Monitor agent performance metrics, identify failure modes, and iterate on prompts, connectors, and skill implementations to continuously improve user experience and business outcomes.

What we look for

Technical

Python ProficiencyAdvanced proficiency in Python for building agent systems, data processing, and backend services. Experience with Python frameworks and libraries commonly used in AI/ML applications and enterprise software development.
AI Agent Framework KnowledgeDeep understanding of modern AI agent architectures and frameworks including agent orchestration patterns, agentic reasoning loops, LLM integration, and evaluation methodologies. Familiarity with agent concepts such as tool use, planning, memory management, and multi-step task execution.
MCP and Integration ProtocolsWorking knowledge of Model Context Protocol (MCP) and similar standards for connecting AI models to external systems. Understanding of when, where, and why to use MCP servers for extending agent capabilities and integrating with enterprise software.
Context Engineering and Prompt DesignAbility to architect effective context engineering strategies that improve agent reasoning and reliability. Experience designing prompts, system instructions, and information architecture that enhance agent decision-making in complex business scenarios.
TypeScript, Go, and Multi-Language DevelopmentExperience with TypeScript and Go for building scalable backend services, APIs, and integrations. Comfortable working across multiple programming languages and selecting the right tool for specific system requirements.
Backend and API DevelopmentStrong experience designing and building scalable backend systems, RESTful APIs, and microservices architectures. Understanding of database design, system design principles, and performance optimization for enterprise applications.
LLM Integration and Prompt EngineeringExperience integrating frontier large language models into production systems. Deep familiarity with latest LLM capabilities, limitations, and techniques for reliable prompt engineering and output processing in critical business workflows.

Education

Bachelor's Degree in Computer Science or Related FieldFormal education in Computer Science, Software Engineering, Mathematics, or related discipline providing foundational knowledge of algorithms, data structures, system design, and computer architecture.

Experience

4+ Years Professional Software EngineeringMinimum four years of professional software engineering experience demonstrating proficiency in building production systems, working with complex codebases, and collaborating effectively within engineering teams. Experience should include building scalable backend systems and working with enterprise or internal platform challenges.
Enterprise or Internal Platform DevelopmentExperience building platforms, tools, or systems for enterprise customers or internal organizational use. Understanding of enterprise requirements, security considerations, reliability expectations, and the challenges of supporting diverse user technical abilities and business workflows.
Daily AI Tool and Model UsageRegular, hands-on experience with frontier AI models and tools in professional and personal contexts. Deep familiarity with current state-of-the-art LLM capabilities, limitations, and rapidly evolving agent technologies that informs product decisions.
Cross-Functional Stakeholder CollaborationExperience collaborating with non-technical stakeholders including business operations, product management, sales, and other business functions. Ability to understand diverse organizational needs and translate business requirements into technical solutions.

Skills

Required skills

PythonProduction-grade Python development for building backend services, AI integrations, and enterprise systems
AI Agent ArchitectureDesign and implementation of multi-step reasoning agents, tool orchestration, and agentic workflows
Backend Systems DesignBuilding scalable, reliable backend systems and APIs that support enterprise workloads
LLM IntegrationIntegrating frontier language models into production systems with proper error handling and reliability patterns
Context EngineeringArchitecting effective context and information structures that improve agent reasoning and decision-making
Product Thinking and User EmpathyUnderstanding end-user needs, designing simple experiences despite technical complexity, and making decisions that prioritize user success
System Integration and ConnectorsBuilding reliable connectors and integrations between AI agents and external business systems

Nice to have

TypeScriptExperience building backend services and APIs with TypeScript, particularly for AI/agent applications
GoExperience with Go for building high-performance backend services and microservices
Model Context Protocol (MCP)Familiarity with MCP specification and implementation for extending AI agent capabilities
Agent Evaluation FrameworksExperience designing evals, metrics, and testing frameworks for agent systems
Business Process AutomationPrior experience automating business processes or building tools for internal operations teams
Enterprise Software ArchitectureFamiliarity with enterprise security, compliance, data governance, and scalability requirements
Vector Databases and EmbeddingsExperience with embeddings, vector search, and retrieval-augmented generation (RAG) for agent context
Prompt Engineering and TuningAdvanced techniques for prompt optimization, few-shot learning, and reliable output formatting

Compensation & benefits

Salary

USD 220,000 – 405,000 (annual)

Stock options

Available

Benefits

Work on Frontier AI Technology

Build systems at the cutting edge of AI agent technology, working with the latest large language models and agentic frameworks that are reshaping enterprise work

High-Impact Internal Adoption

See your work immediately impact Perplexity's internal operations and engineering velocity across recruiting, finance, legal, operations, and go-to-market teams

Enterprise Customer Influence

Translate internal learnings into product improvements that directly benefit Perplexity's growing enterprise customer base

Cross-Functional Collaboration

Partner with product managers, designers, data scientists, and business leaders to solve complex organizational challenges

Rapid Learning Environment

Work in an AI-native company culture where continuous learning about frontier models and agentic patterns is core to daily work

Equity Compensation

Participate in company growth through competitive equity packages alongside base compensation

Interview process

  1. 1
    Initial Screening Call — Conversation with recruiter to understand your background, experience with AI tools, and familiarity with agentic AI concepts. Typical duration: 30 minutes.
  2. 2
    Technical Phone Screen — Deep technical discussion with a member of the engineering team covering your experience building backend systems, LLM integrations, and your understanding of modern AI agent architectures. Expected topics: system design principles, agent frameworks, production backend experience.
  3. 3
    Take-Home Technical Assignment — Design and coding exercise focused on building an AI agent integration or connector. May involve designing context engineering strategies, integrating with an LLM, or architecting a multi-system integration. Typically takes 2-4 hours.
  4. 4
    Technical Deep Dive Interview — On-site or video interview reviewing your take-home assignment and discussing your approach to system design, agent architecture decisions, and trade-offs. Interview with 1-2 senior engineers from the Enterprise Adoption team.
  5. 5
    Product and Cross-Functional Discussion — Conversation with product manager and/or business stakeholder to assess your product judgment, ability to understand non-technical user needs, and empathy for how different business functions work. This evaluates your ability to collaborate cross-functionally.
  6. 6
    Leadership and Values Alignment — Final round with a member of leadership to discuss your career goals, learning interests, collaboration style, and alignment with Perplexity's mission in building the agentic future of enterprise work.
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Perplexity AI

Perplexity AI

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Perplexity AI is an AI-powered answer engine that delivers accurate and up-to-date information by leveraging advanced language models and web search.

San Francisco, CA, USAFounded 2021perplexity.ai

Tech Stack

Languages
PythonTypeScriptGo
Frameworks
FastAPILangChainLlamaIndexPydantic
Databases
Vector Databases (Pinecone, Weaviate, Qdrant)PostgreSQLRedis
Tools
Git / GitHubDockerKubernetesModel Context Protocol (MCP)OpenAI API, Anthropic API
Other
Agentic AI ArchitectureRetrieval-Augmented Generation (RAG)Prompt Engineering and OptimizationAgent Evaluation and EvalsEnterprise Integration Patterns
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