Offensive Security Engineer

About the company

ClickHouse provides a fast, open-source columnar database and managed cloud service designed for real-time analytics, data warehousing, observability, and AI/ML workloads.

About this role

<div class="content-intro"><h3>About ClickHouse</h3> <p>Recognized on the 2025 Forbes Cloud 100 list, ClickHouse is one of the most innovative and fast-growing private cloud companies. With more than 4,000 customers and ARR that has grown over 250 percent year over year, ClickHouse leads the market in real-time analytics, data warehousing, observability, and AI workloads.</p> <p>The company’s sustained, accelerating momentum was recently validated by a $400M Series D financing round. Over the past three months, customers including Capital One, Lovable, Decagon, Polymarket, and Airwallex have adopted the platform or expanded existing deployments. These customers join an established base of AI innovators and global brands such as Meta, Cursor, Sony, and Tesla.</p> <p>We’re on a mission to transform how companies use data. Come be a part of our journey!</p></div><h4><strong>About the team</strong></h4> <p>The Security Team is responsible for providing key security capabilities covering application, cloud and enterprise security, incident response, detection and GRC. Our team is looking for an experienced, hands-on security practitioner, who will drive the adoption of modern security processes and tooling, with focus on supporting our engineering and product teams in improving the security posture of our platforms and services.</p> <h4><strong>What you will do:</strong></h4> <ul> <li>Identify security gaps and vulnerabilities in all ClickHouse offerings triage a wide range of vulnerabilities reported via our bug bounty program, responsible disclosure, GitHub Issues covering web, API and server - client assets including low level memory issues like heap or buffer overflows</li> <li>Improve and develop security assurance activities - pentests, vulnerability assessments, bug bounty programs, fuzzing</li> <li>Plan and execute internal red team assessments and penetration tests against ClickHouse infrastructure, cloud environments, designing realistic adversary scenarios to test detection, response and control effectiveness</li> <li>Assess AI/LLM-specific attack surface across ClickHouse's own AI-powered features and internal AI tooling, including prompt injection, model/data exfiltration, and unsafe agentic tool-use patterns</li> <li>Build and operate agentic tooling for reconnaissance, exploit-chaining and attack-path discovery, and apply LLM-assisted fuzzing to accelerate vulnerability discovery across ClickHouse's products and infrastructure</li> <li>Partner with detection engineering to validate and improve detection coverage during red team exercises, measuring and reporting on control effectiveness and time to detect/respond</li> <li>Handle information security events and incidents across ClickHouse products and services</li> <li>Develop processes, tooling and automation to scale security processes and mitigate risks to the business</li> </ul> <h4><strong>What you bring along:</strong></h4> <ul> <li>7+ years of experience in pentesting, red teaming and product security</li> <li>Experience supporting engineering and product implementation efforts by performing threat assessments, assurance activities, advisory as well as, in some cases, implementation work across distributed systems covering web, API, client/server assets</li> <li>Hands-on experience conducting offensive security engagements - internal red teaming, penetration testing and adversary simulation - across cloud, network and application environments</li> <li>Ability to design adversary scenarios grounded in real threat intelligence (e.g. ransomware operators, supply chain attackers, insider threat) tailored to ClickHouse's risk profile as a multi-tenant cloud data platform</li> <li>Strong written and verbal communication skills, with ability to translate attack chains into clear, actionable findings for engineering and leadership</li> <li>Experience building or adapting agentic and LLM-assisted tooling for offensive security use cases (recon automation, exploit chaining, fuzzing harnesses), with judgment on where AI genuinely speeds up an engagement versus adds noise</li> <li>Familiarity with AI/LLM-specific vulnerability classes and testing methodology</li> <li>Strong knowledge of and experience with one or more cloud service providers (e.g. AWS, GCP, Azure), Kubernetes, Cilium</li> <li>Experience implementing and operating engineering security tools and processes (e.g. static / dynamic code analysis, software composition analysis, SBOM, OWASP SAMM, client and network fuzzing tools)</li> <li>Security as code mindset, with focus on solving problems with automation and scale in mind</li> </ul> <h4><strong>Bonus Points:</strong></h4> <ul> <li>BS, MS, or PhD in Computer Science or related field</li> <li>Previous contributions to open source projects</li> <li>Security or cloud related certifications (AWS, GCP, Azure)</li> <li>Previous experience in using AI security harnesses for pentesting purposes</li> <li>Experience building or operating internal red team tooling and infrastructure from scratch, rather than relying solely on off-the-shelf frameworks</li> <li>Offensive security certifications (e.g. OSCP, OSCE, OSEP, OSWE)</li> </ul><div class="content-conclusion"><h3><strong>Compensation</strong></h3> <p><span style="font-weight: 400;">For roles based in the&nbsp;<strong>United States</strong>, t</span>he typical starting salary range for this position is listed above. In certain locations, such as the San Francisco Bay Area and the New York City Metro Area, a premium market range may apply, as listed.</p> <p class="p1">These salary ranges reflect what we reasonably and in good faith believe to be the minimum and maximum pay for this role at the time of posting. The actual compensation may be higher or lower than the amounts listed, and the ranges may be subject to future adjustments.</p> <p class="p1">An individual’s placement within the range will depend on various factors, including (but not limited to) education, qualification