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Application Security Researcher

OX Security

Application Security Researcher

ArgentinaRemoteFull-time

Posted Oct 1

Apply

Job Description

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

Job Description

Description

About the Position

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

Job Description

Description

About the Position

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

Job Description

Description

About the Position

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

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What You'll Bring

What You'll Bring

What You'll Bring