---
title: 'Member of Technical Staff (Software Engineer, Enterprise Agent Evals & Efficiency) at Perplexity'
canonical: 'https://feeny.ai/job/member-of-technical-staff-software-engineer-enterprise-agent-evals-efficiency-k2txz5wzrt1g'
type: 'job'
last_seen: '2026-11-08'
---

# Member of Technical Staff (Software Engineer, Enterprise Agent Evals & Efficiency) at Perplexity

- **Company:** [Perplexity](https://feeny.ai/companies/perplexity)
- **Location:** San Francisco, CA
- **Compensation:** $220k–$405k
- **Employment:** full-time
- **Posted:** 2026-10-19
- **Last confirmed live:** 2026-11-08
- **Apply:** https://jobs.ashbyhq.com/Perplexity/f3814af2-55a3-49a5-b0cb-67199a2a45fb

## Job description

## About the Role

The Enterprise Agent Evals & Efficiency team makes Perplexity's agents better at completing real work across enterprise connectors, tools, and data. Our goal is to help agents choose the right tools, use the right context, and complete complex workflows reliably, with less time and compute. This team owns the improvement loop: define what successful work looks like, build evaluations that measure it, understand where agents fail, and ship changes that improve outcomes. This is a hands-on engineering role with end-to-end ownership, from building realistic enterprise evaluation environments to shipping improvements across the agent harness, tools, and skills. You'll create complex scenarios spanning connected systems, data, and permissions, use them to identify where agents struggle, and improve the tools agents call, the skills they follow, the context they receive, and the models they use. Working with AI Research, Connectors, and Platform teams, you'll turn experimental results into measurable gains in task success, latency, and cost per successful task. The goal is not just to measure agents, but to make more enterprise work reliable and practical to automate.

## Key Responsibilities

- Build realistic enterprise evaluation environments spanning connected applications, representative datasets, user roles, and permissions, with complex, multi-step workflows and reproducible system state.
- Own evaluation infrastructure, task suites, and automated graders that measure how well agents complete enterprise work, calibrated against human judgment and grounded in end-to-end outcomes.
- Analyze agent trajectories and production failures, identify root causes, and ship improvements across the agent harness, tools, and skills that measurably improve task success and reliability.
- Develop reusable skills and improve tool descriptions, schemas, and result handling so agents can select the right tools, execute workflows correctly, and recover from errors with fewer unnecessary calls.
- Build and evaluate model-selection and routing strategies that match each task to the right model and effort level, balancing quality, latency, reliability, and cost.
- Improve agent efficiency through context management, skill loading, caching, and execution strategies that reduce wasted tokens and cost per successful task without compromising quality or safety.
- Build regression gates and launch-readiness signals for model, connector, tool, skill, and harness changes, and validate that evaluation gains translate into better production outcomes.

## Qualifications

- 5+ years of software engineering or machine learning engineering experience, with a track record of owning complex production systems from design through deployment and operation.
- Strong system design skills, including building reliable, scalable infrastructure for experimentation, evaluation, or data-intensive applications.
- Strong proficiency in a backend language such as Python, Go, or Rust, and the ability to work effectively across a multi-language production stack.
- Hands-on experience building, evaluating, or improving LLM-based applications or agents, including tool use and multi-step workflows.
- Deep expertise in at least one of the following:
- Evaluation infrastructure, benchmark design, and automated grading.
- Agent harnesses, tool interfaces, and reusable skills for complex workflows.
- Realistic test environments or simulations spanning multiple systems, datasets, permissions, and stateful workflows.
- Model selection, routing, and inference efficiency, including context management and caching.
- Strong experimental and statistical judgment, including choosing representative tasks, defining meaningful success criteria, diagnosing failures, and distinguishing real improvements from noise.
- Sound technical judgment in balancing task quality, latency, reliability, and cost, with a track record of translating evaluation findings into shipped improvements.
- A track record of leading ambiguous, cross-team initiatives from architecture through production adoption, setting technical direction, 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.

## About Perplexity

## Company Overview
- **One-liner**: Perplexity builds an AI-powered answer engine that delivers accurate, real-time answers to any question, serving curious minds and professionals who demand precision and speed.
- **Entity Type**: Private (total funding $1.7B across 16 rounds)
- **Headquarters**: San Francisco, California, United States
- **Founded**: 2022
- **Founders**: Aravind Srinivas, Denis Yarats, Johnny Ho, Andy Konwinski

## Core Business
- **Primary industry**: AI-powered search and knowledge retrieval, Software Development
- **Target customers**: B2C (general users), B2B (enterprise API customers), and power users seeking reliable information
- **Mission**: “AI for people who expect more – more accuracy, more agency, more signal, less noise.”

## Products & Services
- **Perplexity AI (Free Tier)**: Real-time conversational search engine that synthesizes web results with citations, accessible via web and mobile app. *Type*: SaaS
- **Perplexity Pro**: Subscription offering enhanced features such as advanced AI models, multimodal search, and increased usage limits. *Type*: SaaS (subscription)
- **Perplexity API Platform**: Enables developers to integrate Perplexity’s search and reasoning capabilities into their own applications. *Type*: API
- **Perplexity Browser Extension**: Brings AI-powered search directly into the browser for quick answers without leaving the page. *Type*: Browser extension

## Market Standing
- **Valuation/Market Cap**: Not publicly available in provided sources (prior reports indicate ~$9B valuation as of 2024, but not confirmed in this data set)
- **Key Metric**: Total funding $1.7B (16 rounds); annual revenue ~$50M (LinkedIn estimate)
- **Notable Investors/Partners**: Not explicitly listed in provided search results; widely known investors include IVP, NEA, Jeff Bezos, and others (not sourced here)
- **Growth Signals**: Headcount grew 11.3% YoY to 1,152 employees; operates in 54 countries; LinkedIn followers grew 131.8% yearly to >1.6M; active hiring across 48+ open roles including AI Research, Engineering, and Go-to-Market teams

## Competitive Advantages
- **Real-time, cited answers**: Unlike traditional chatbots, Perplexity grounds answers in live web results with transparent sources, building trust and accuracy.
- **Multimodal and agentic capabilities**: Continuously pushes frontier research (e.g., query-aware context compression, agents for knowledge work) that differentiates from generic LLM interfaces.
- **Vertical integration from research to product**: In-house AI research team tackles open problems unique to Perplexity’s scale, enabling fast iteration on novel methods.
- **Strong brand and user base**: Rapid consumer adoption with millions of monthly active users and high engagement.

## Strategic Focus
- **Pushing the frontier of search**: Evolving from retrieval services to code generation, agents, and full autonomy in knowledge work.
- **Expanding enterprise and API revenue**: Growing B2B footprint with API platform and enterprise solutions.
- **Global hiring and office expansion**: Offices in San Francisco, Palo Alto, New York, Austin, Washington D.C., London, Berlin, and Belgrade, with “4 days in office” hybrid model.
- **Investing in AI research**: Dedicated research division (Perplexity Research) exploring reasoning, agents, and systems to redefine how people navigate the internet.

## Why Work Here
- **Culture & Environment**: “Thoughtful support” culture with emphasis on craftsmanship, ownership, entrepreneurship, scholarship, and partnership. Hybrid schedule (4 days in-office) based on location.
- **Perks**: Daily catered meals (breakfast, lunch, dinner in office), office snacks, ride home program, commuter benefits, home office reimbursement, fitness classes, gym memberships.
- **Compensation & Benefits**: Competitive salary and equity packages; retirement plans with company match; flexible PTO; holiday shutdown between Christmas and New Year; 12 weeks paid bonding leave; comprehensive health, dental, and vision insurance.
- **Relocation & Visa Support**: Relocation assistance and visa/green card sponsorship for eligible roles. Partners with immigration firm to support the process.
- **Engineering Excellence**: “Technical assessment for relevant roles”; values hands-on contribution, broad skill sets, and merit-based evaluation. Frequent Tech Talks and exposure to greenfield AI research problems.

## Sources
1. [perplexity.ai/hub/careers](https://www.perplexity.ai/hub/careers)
2. [jobs.ashbyhq.com/perplexity](https://jobs.ashbyhq.com/perplexity)
3. [perplexity.ai](https://www.perplexity.ai/)
4. [linkedin.com/company/perplexity-ai](https://www.linkedin.com/company/perplexity-ai)
5. [research.perplexity.ai](https://research.perplexity.ai/)

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