---
title: 'Software Engineer - Anti-Abuse at Arena Intelligence, Inc.'
canonical: 'https://feeny.ai/job/software-engineer-anti-abuse-arena-intelligence-inc-united-states-af0j0c7eaekc'
type: 'job'
last_seen: '2026-09-18'
---

# Software Engineer - Anti-Abuse at Arena Intelligence, Inc.

- **Company:** Arena Intelligence, Inc.
- **Location:** United States
- **Employment:** full-time
- **Work type:** hybrid
- **Posted:** 2026-04-22
- **Last confirmed live:** 2026-09-18
- **Apply:** https://jobs.ashbyhq.com/arena/76fcd272-2f5b-4405-ae6c-577f7b4ccd2b/application

**Skills:** Production Software Engineering, SQL, Data Analysis, Node.js, TypeScript, Python, Go, Backendpoint security, Trust and Safety, Anti-abuse, Anti-fraud, Anti-spam, LLM-specific adversarial inputs, Jailbreaks, Prompt injection, Agent safety, Browser-automation abuse, LLM-API abuse, Voting platform security, Rating system security

> The Security Engineer, Anti-Abuse owns platform misuse end-to-end, building detection, enforcement, and investigation systems to protect Arena Intelligence's AI evaluations. This founding role involves designing defenses against automated abuse, integrating with policy and product teams, and ensuring the trustworthi...

## Job description

## About Arena Intelligence

Arena is the platform for evaluating how AI models perform in the real world. Founded by researchers from UC Berkeley's SkyLab, we're on a mission to measure and advance the frontier of AI for real-world use, and to build the foundation for everyone to understand, shape, and benefit from it.

Tens of millions of people use Arena each month to evaluate how frontier systems handle the work they actually do. The preferences they share power the most transparent, rigorous, and human-centered evaluations in AI. Leading AI labs, enterprises, and independent researchers rely on our work and open datasets to understand how models behave in real workflows: agentic coding, creative generation, professional productivity, and beyond. We go beyond leaderboards and decompose what human experience reveals about AI, so models advance toward the work people actually do.

We're a team of researchers, academics, builders, and creatives from UC Berkeley, Google, Stanford, and DeepMind. We seek truth, move fast, and value craftsmanship, curiosity, and impact over hierarchy. We're building a company where thoughtful, curious people from all backgrounds can do their best work together, in an office culture that radiates excellence, energy, and focus.

## About the Role

Arena Intelligence is seeking a Software Engineer - Anti-Abuse to own platform misuse end-to-end. Arena's evaluations are only as trustworthy as the signal behind them — and that signal is under constant, creative attack. You will build the detection, enforcement, and investigation systems that keep Arena's leaderboards trustworthy, stop automated abuse across our services, and defend against the full spectrum of AI-era harms. This is a founding builder role. You will set the strategy, write the code, and build the platform that future abuse, integrity, and trust & safety hires grow on top of. You'll work shoulder-to-shoulder with product, infrastructure, model partners, policy, and leadership, and you'll be accountable for outcomes the whole company can see: is the leaderboard clean, are harmful uses caught, are our services safe to ship?

You’ll

- Own the abuse vision for Arena: what gets detected, what gets enforced, how fast, and with what false-positive budget
- Design and operate detection for bots, sybils, coordinated inauthentic voting, and rating-system manipulation — the integrity of Arena's leaderboards is the product
- Build enforcement primitives (rate limits, challenges, shadowbans, account actions, model-side refusals) that are reversible, auditable, and humane
- Detect and mitigate inference abuse and cost exploitation at the platform layer
- Build jailbreak and multi-provider misuse detection across the models Arena serves, and partner with model-provider trust & safety teams on signal-sharing and escalation
- Scope and implement abuse monitoring for every new product launch — web search, web fetch, live site deployment, and whatever's next — as part of the launch checklist, not after the fact
- Prototype and mature into production systems of detection, review, and enforcement for the highest-severity harms (CSAM/NCII, violent extremism, self-harm), including the legal reporting pipeline (e.g., NCMEC)
- Build internal investigator tooling so policy, on-call, and future T&S analysts can triage incidents without engineering bottleneck
- Partner with Security on shared surface — account takeover, credential stuffing, API-key abuse, and the identity/behavioral-signal platform
- Partner with policy, legal, and leadership on acceptable-use policy, enforcement escalations, and public-integrity narrative

You’ll have

- 6+ years of production software engineering experience, including building and operating systems under adversarial conditions
- Shipped experience in at least one of: trust & safety, anti-abuse, anti-fraud, anti-spam, integrity, or risk engineering
- Strong SQL and data-analysis skills — this role is 30%+ pattern-finding and investigation, not just shipping code
- Adversarial and investigative mindset — you can articulate a novel attack before designing the defense, and follow evidence when a novel harm surfaces
- High judgment on false-positive cost, user harm, and the reversibility of enforcement actions
- Proficiency in a modern backend language (Node.js, TypeScript, Python, or Go)
- Excellent communication — you'll build alignment with engineering, product, policy, and leadership routinely

Bonus Points

- Experience with LLM-specific adversarial inputs — jailbreaks, direct and indirect prompt injection, tool-use abuse
- Experience with agent safety, browser-automation abuse, or LLM-API abuse
- Background in securing voting, rating, reputation, or marketplace platforms against coordinated manipulation
- ML or ML-systems experience — feature engineering, online/offline evaluation, label acquisition, drift handling
- Experience building investigator or analyst tooling used by non-engineers
- Contributions to open-source trust & safety, abuse-detection, or adversarial-ML work
- Background in gaming integrity, ad-fraud, or financial-crime engineering at scale

## What we offer

- We offer competitive compensation and equity aligned to the markets where our team members are based. The base salary range will depend on the candidate’s permanent work location.
- Comprehensive health and wellness benefits, including medical, dental, vision, and additional support programs.
- The opportunity to work on cutting-edge AI with a small, mission-driven team
- A culture that values transparency, trust, and community impact

Come help build the space where anyone can explore and help shape the future of AI.

Arena Intelligence provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, national origin, age, disability, genetics, sexual orientation, gender identity, or gender expression. We are committed to a diverse and inclusive workforce and welcome people from all backgrounds, experiences, perspectives, and abilities.

## About Arena Intelligence, Inc.

## Company Overview
- **One-liner**: Arena Intelligence, Inc. (formerly LMArena/Chatbot Arena) operates a public, community-driven platform for evaluating large language models through anonymous head-to-head comparisons and voting.
- **Entity Type**: Private (Series A, total $250M funding)
- **Headquarters**: San Francisco, California, United States
- **Founded**: 2025 (company incorporation; platform launched April 2023)
- **Founders**: Wei-Lin Chiang, Anastasios N. Angelopoulos, Ion Stoica

## Core Business
- **Primary industry**: AI evaluation and research infrastructure
- **Target customers**: AI labs (OpenAI, Google DeepMind, Anthropic, DeepSeek), enterprises, researchers, and the general AI community (B2B and B2C)
- **Mission**: Fuel the world’s most trusted AI evaluation platform, using real-world community votes to benchmark model performance

## Products & Services
- **LMArena Platform**: Public web-based platform where users enter prompts for two anonymous models, vote on the better response, and then see the models’ identities. Supports text, vision, web dev, search, video, and image modalities. Over 50 million votes collected.
- **Max (Model Router)**: An intelligent orchestrator that routes each user prompt to the most capable model for that specific prompt, powered by 5+ million real-world votes.
- **Enterprise Evaluation Product**: Launched September 2025, provides rigorous, reproducible evaluations for AI labs and enterprises, generating actionable feedback on model performance.

## Market Standing
- **Valuation/Market Cap**: Not publicly disclosed
- **Key Metric**: $100M annualized revenue run rate as of June 2026 (achieved within 8 months of enterprise offering launch)
- **Total Funding**: $250M (Seed $100M led by Andreessen Horowitz and UC Investments in June 2025; Series A $150M led by Felicis and UC Investments in January 2026)
- **Notable Investors/Partners**: Felicis, UC Investments, Andreessen Horowitz, The House Fund, LDVP, Kleiner Perkins, Lightspeed Venture Partners, Laude Ventures
- **Growth Signals**: Community grew 25x in one year; 50 million votes, 400+ model evaluations, 145k open-source battle data points; operates in 5 countries (US, Germany, UK, UAE, Canada); headcount of 49 with +10.5% monthly growth

## Competitive Advantages
- **Community-driven data**: Trusted by major AI labs for real-world, reproducible evaluations; 10M+ community members contribute diverse prompts and votes
- **First-mover & brand**: The de facto public leaderboard for LLM comparison; used for pre-release model testing (e.g., DeepSeek R1, GPT-5 "summit", Gemini 2.5 Flash Image "Nano Banana")
- **Open science**: Academic partnerships program funding independent research on AI evaluation methodology
- **Revenue velocity**: Achieved $100M ARR in under a year from enterprise launch, indicating strong product-market fit

## Strategic Focus
- Scale the platform with new features and modalities (video, search, web dev)
- Deepen enterprise offerings and model routing capabilities (Max)
- Expand academic partnerships to advance the science of AI evaluation
- Continue to serve as the gold standard for real-world model performance benchmarking

## Why Work Here
- **Culture**: Fast-moving, research-driven startup with roots at UC Berkeley; emphasis on community, open source, and rigorous science
- **Team**: 49 employees, 41% technical (Data Engineers, ML Scientists, ML Engineers, Software Engineers), with talent from top AI labs and universities (Berkeley RISE Lab, Google, Apple)
- **Growth**: High-growth environment (revenue run rate doubled rapidly, headcount growing ~10% monthly)
- **Location**: Headquarters in San Francisco (2261 Market St., Ste 85064); offices also in SF (two additional locations). Likely hybrid/office-based given SF HQ and local employee concentration.
- **Perks**: Not explicitly listed, but typical for VC-backed startup (equity, competitive comp, impact on foundational AI infrastructure)

## Sources
1. [arena.ai](https://arena.ai/)
2. [arena.ai/blog/series-a](https://arena.ai/blog/series-a/)
3. [linkedin.com/company/arenaai](https://www.linkedin.com/company/arenaai)
4. [jobs.ashbyhq.com/arena](https://jobs.ashbyhq.com/arena)

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