CodeRabbit is the leading AI code review platform, trusted by more than 17,000 customers and 150,000 open-source projects, conducting over 2 million code reviews each week. We build the symbiotic partnership between developers and AI that makes shipping fast software safe again, reviewing every pull request, IDE change, and CLI commit so teams can move quickly without breaking things.
We are a fast-moving, well-funded company, fresh off a $143M Series C at a $1.5B valuation — building Agentic Change Management, the control layer for software changes created by humans and agents. As AI writes more of the world's code, the bottleneck moves from implementation to judgment and helping human judgment scale is exactly the problem we exist to solve.
We're hiring a strong, hands-on Product Manager to own CodeRabbit's security product: the AI-driven scanner that hunts for real vulnerabilities across entire codebases and surfaces security findings directly in pull request reviews. The product combines LLM-based vulnerability hunting with static analysis, secrets detection, infrastructure-as-code checks, and dependency and supply-chain analysis, and grades every finding for exploitability and severity before a customer ever sees it.
This is a high-ownership IC role.
One thing we're firm on: you must come from the security space. This product lives or dies on security judgment - what a true positive looks like, what severity a finding deserves, and what an AppSec team actually needs before it will trust a scanner.
Own the security product end to end: deep codebase scans, security findings in pull request reviews, and everything in between
Decide which vulnerability classes, scanner capabilities, and languages we invest in next across SAST, secrets detection, infrastructure-as-code misconfiguration, and dependency and supply-chain analysis
Define what good detection means as a product: the precision, recall, and noise bar a finding must clear before a customer sees it
Own how findings are presented, triaged, and resolved: severity and exploitability grading, dismissal and feedback loops, remediation flows, and reporting
Treat every false positive as a trust problem, not a tuning detail — the goal is a scanner developers believe, not one they mute
Turn detection-quality evidence (benchmarks, evaluations, real-world results) into product decisions and customer-facing proof
Own the AppSec and CISO persona alongside our developer users: what security teams need to evaluate, trust, and roll out the product across an organization
Partner with Sales on enterprise security evaluations and competitive positioning in the code security market
Shape pricing and packaging of the security offering with Growth and Finance
Work daily with the engineers building the agentic scanning pipeline; bring the customer and market view to detection priorities
Own the quality bar for what ships: hold detection changes to benchmark evidence, and make precision-versus-coverage tradeoffs deliberately rather than by default
5–8 years in the security space: product management at a security vendor, or hands-on security work (application security, penetration testing, vulnerability research, detection engineering) that you carried into product. We're hiring security depth, not adjacent experience
Product management experience with deeply technical products, ideally at a B2B SaaS or developer tools company
Practical knowledge of real vulnerability classes and how they're exploited — enough to challenge a severity call, judge a disputed false positive, and hold your own with security engineers and customers' AppSec teams
You know the security tooling landscape (SAST, DAST, secrets scanning, IaC, software composition analysis) and exactly why developers distrust most of it
Technically fluent. You can read code, understand APIs, and have detailed conversations with engineers without a translator
You write well and communicate precisely. PRDs and tickets you've written are things you're proud of
Comfortable with ambiguity; can move from fuzzy problem to clear spec without hand-holding
Low ego, high ownership. You care about the outcome more than the credit
A hands-on practitioner past: CVEs, bug bounty history, CTFs, or pentest findings with your name on them
Experience shipping products built on LLMs or agentic systems, or well-formed judgment about where they help and where they fail
Direct vendor-side experience in the code security market (SAST, ASPM, or software composition analysis)
Working knowledge of Git platforms (GitHub, GitLab, Bitbucket, ADO) as a power user or PM
We'll be upfront: this isn't a compliance-checkbox product, and it isn't a GTM-only role. The hard problems here are detection quality, trust, and making security findings genuinely actionable for developers - deep, technical, judgment-heavy product work in one of the fastest-moving areas of AI.
What it is: one of the biggest product bets we're making. As AI writes more of the world's code, someone has to catch what it gets wrong, and we intend to be the ones developers and security teams both trust to do it.
🤝 Collaborative Humans: Prioritizing collective intelligence
🚀 Fearless Innovators: Turning obstacles into growth opportunities
💪 Persistent, Passionate Developers: Thriving on complex, long-term challenges
🎯 Impact-Driven Creators: Crafting intuitive tools for developers
🧠 Rapid Learners and Un-learners: Adapting quickly in our fast-paced technological world
Work on cutting-edge technology with real-world impact
Collaborative and innovative environment
Competitive salary, equity, and benefits
Professional development opportunities
To apply, submit your resume and relevant project samples or GitHub profiles. CodeRabbit is an equal-opportunity employer committed to diversity and inclusion.
Job details are sourced from the employer's original posting.
Open job postingAbout the company
CodeRabbit is an innovative research and development company focused on building extraordinarily productive human-machine collaboration systems. Our primary goal is to create the next generation of Gen AI-driven code reviewers: a symbiotic partnership between humans and advanced algorithms that significantly outperforms individual engineers. We combine language models with human ingenuity to push the boundaries of software development efficiency and quality.