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Rogo

Generative AI for financial research automation

Security Engineer - Product

Offensive Security & TestingConfirmed live in the last 24 hours
Full-timeNew York, NY, USA$270k - $330k /yrIn-person

About the Job

Requirements

  • Professional penetration testing experience across web applications, APIs, and cloud environments; AI/ML security experience is desirable.
  • Professional development experience in a strongly typed language such as Rust, Go, Java, or C++, alongside scripting languages such as Python or Bash.
  • Ability to use Burp Suite, Nuclei, Semgrep, custom fuzzing frameworks, and develop custom tools.
  • Experience integrating automated security checks, including software composition analysis, static application security testing, and dynamic application security testing, into continuous integration and continuous delivery pipelines.
  • Comfort with infrastructure automation using Terraform and Kubernetes, and ability to identify misconfigurations and attack paths in AWS or Google Cloud Platform environments.
  • Applied knowledge of threat modeling, cryptography fundamentals, and compliance frameworks such as SOC 2, ISO 27001/42001, and NIST Cybersecurity Framework.

Responsibilities

  • Conduct continuous hands-on penetration testing and red team assessments against applications, APIs, AI/ML pipelines, and cloud environments.
  • Build agentic security tooling to find, validate, and patch vulnerabilities across code review, dependency management, and infrastructure as code.
  • Develop and maintain custom offensive tools, exploit chains, and attack simulations tailored to the AI platform and its architecture.
  • Build and operate automated security testing and remediation pipelines that scale offensive coverage.
  • Perform adversarial testing of AI attack surfaces, including prompt injection, model manipulation, data poisoning, agent-based workflows, and tenant isolation boundaries.
  • Research vulnerabilities and hunt for bugs, logic flaws, authentication bypasses, and chained exploits beyond automated scanner findings.
  • Design and execute threat modeling sessions with engineering teams and translate findings into prioritized remediation.
  • Build attack simulation environments and continuously validate security controls against real-world tactics, techniques, and procedures and customer-driven penetration test scenarios.
  • Contribute directly to backend codebases, fix critical vulnerabilities, harden authentication and authorization flows, and build security primitives into the platform.
  • Lead purple team exercises with infrastructure and engineering teams to test detection and response capabilities.
  • Manage relationships with external penetration testing firms and drive remediation of findings to closure.
  • Share offensive tradecraft, emerging attack techniques, and lessons learned with engineering and leadership.

Desired Qualifications

  • Experience building or interest in building agentic security tooling that autonomously finds, validates, and patches vulnerabilities.
  • Experience testing multi-tenant software-as-a-service platforms serving regulated industries, especially financial services.
  • Hands-on cloud penetration testing experience in AWS or Google Cloud Platform, including privilege escalation, cross-account attacks, and metadata abuse.
  • Kubernetes security testing experience, including role-based access control abuse, container escapes, admission controller bypasses, and network policy evasion.
  • A bug bounty track record or published common vulnerabilities and exposures or security research.
  • Experience in customer-facing security conversations, deep-dive technical sessions, penetration test debriefs, and security architecture reviews.
  • OSCP, OSWE, GXPN, GWAPT, CPTS, or similar offensive security certifications.

About the Company

Rogo

Generative AI for financial research automation

Rogo builds a generative AI platform for financial institutions to automate research, workflows, and document creation by coordinating multiple AI models across proprietary and external content. Its model-agnostic orchestration lets users plug in different AI models and data sources to generate insights, reports, and outputs for analysts, traders, and portfolio teams. The platform serves investment banks, private equity, hedge funds, and asset managers, with deployments across 50,000+ professionals in 350+ firms, and it is expanding into wealth management and new regions in EMEA and APAC. Its goal is to help financial institutions scale research and documentation workloads and speed up decision-making by providing a flexible AI backbone that coordinates models, data feeds, and documents, differentiating through cross-model orchestration tailored to finance.

Company size
201-500
Company stage
Late Stage VC
Total funding
$345M
Headquarters
New York City, New York
Founded
2021

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