Application Security Researcher

Description

About the Position

OX Security secures the AI-driven SDLC from prompt to production. We eliminate critical, real-time risks from AI code generation through cloud runtime by doing what conventional tools can’t: unifying development and cloud context to stop vulnerabilities right at the source. At OX, we’re building the future of cyber security for the AI era. If you’re looking to work on disruptive technology with an amazing team, you belong here.

We’re looking for a highly skilled Application Security Researcher to join our Security Research group and help us push the boundaries of modern AppSec. This is a critical, hands-on role where you’ll work closely with engineers, researchers, and AI & data scientists to build the next generation of application security - including autonomous, agentic pen testing capabilities.

This is not a typical AppSec role. You’ll be building, breaking, and redefining how offensive security works at scale.

Responsibilities

What You’ll Be Doing

• Research vulnerability chaining, business-logic flaws, and complex attack paths across applications and infrastructure
• Design and build detection engines and decision-making logic for autonomous security systems
• Evaluate AI models for application security use cases, measuring where they perform and where they fall short
• Prototype, build, and ship security capabilities into production environments
• Analyze large-scale security data to uncover exploitable attack paths and improve detection accuracy
• Partner with Product, Engineering, and Data teams to shape the next generation of security features
• Help set the team's research direction and own initiatives end to end, from idea to shipped capability

Requirements

What You'll Bring

• M.Sc. in Computer Science, Cyber Security, or a related field
• 5+ years of hands-on experience in offensive security, vulnerability research, or application security
• Deep understanding of web application and API vulnerabilities, including business-logic flaws and multi-step attack chains
• Strong coding skills in Python, Go, or a similar language, with experience shipping production-quality code
• Experience building or tuning detection logic (SAST, DAST, SCA, secrets, or custom rule engines) and reducing false positives
• Solid grasp of modern application and infrastructure stacks: CI/CD pipelines, containers, Kubernetes, and at least one major cloud provider
• Hands-on experience using LLMs or AI models for security tasks, and the judgment to measure where they help and where they fail
• Comfort working with large datasets (SQL, BigQuery, or similar) to drive research and measure detection accuracy
• Ability to take a research idea from prototype to production with minimal guidance
• Clear written communication: you can explain a complex attack path to engineers and product managers

Nice to Have

• Published research, CVEs, conference talks, or bug bounty track record
• Experience building AI agents or evaluation frameworks for LLMs
• Background in exploit development, red teaming, or penetration testing
• Experience with code analysis techniques (taint analysis, call graphs, reachability)
• Contributions to open-source security tools

Originally posted on Himalayas