Lead Security Engineer

JPMorgan Chase JPMorgan Chase · Banking · Singapore · Corporate Sector

Lead Security Engineer role at JPMorgan Chase focused on delivering secure software solutions. The role involves applying AI capabilities to enhance security engineering workflows, including threat modeling, vulnerability analysis, and code review, within a regulated fintech environment. Responsibilities include defining security requirements, triaging threats, developing secure code, and conducting vulnerability assessments.

What you'd actually do

  1. Uses enterprise-authorized AI capabilities within the work environment to accelerate threat modeling, vulnerability analysis synthesis, and security documentation, validating outputs and ensuring sensitive data is handled appropriately.
  2. Minimizes security vulnerabilities by following industry insights and governmental regulations to continuously evolve security protocols, including creating processes to determine the effectiveness of current controls
  3. Conducts discovery, vulnerability, penetration testing, and threat scenarios on multiple organizational assets to identify and assess if vulnerabilities are present, and executes threat modeling for multiple applications including external applications interacting with the internal JPMorganChase network
  4. Applies reuse-first, AI-assisted practices within SDLC/toolchain routines to strengthen security testing and control validation, ensuring traceability/auditability and alignment to resiliency and security expectations.

Skills

Required

  • Bachelor’s Degree in Computer Science, Cybersecurity, Data Science, or related disciplines
  • Formal training or certification on software engineering concepts and 5+ years applied experience.
  • Experience planning, designing, building and implementing enterprise level security engineering products and solutions in a public cloud environment (i.e. AWS, GCP, Azure)
  • Advanced in one or more programming languages/scripts (i.e. C/C#, Python, PowerShell)
  • Advanced knowledge of secure software application development and technical processes with considerable in-depth knowledge in one or more technical disciplines (e.g., cloud, artificial intelligence, machine learning, mobile, etc.)
  • Demonstrated experience using enterprise-authorized AI capabilities within the work environment to support security engineering workflows with strong validation habits and awareness of data sensitivity
  • Ability to review and validate AI-assisted code/security recommendations before adoption, escalating uncertainty and ensuring outcomes align to security, resiliency, and auditability expectations
  • Experience with continuous integration and continuous deployment (CI/CD) tools (Jenkins), version control tools (BitBucket, Git), managing and tracking work using management tools like Jira
  • Experience building security engineering products and solutions
  • Experience working with vendors to assess the sufficiency of their security practices and controls meet industry standards.
  • Experience with threat modelling of applications or architectures using models such as STRIDE.
  • Ability to tackle design and functionality problems independently with little to no oversight

Nice to have

  • Experience within Cyber Security is preferred
  • Excellent communication and presentation skills
  • Prior experience in finance industry is a huge plus

What the JD emphasized

  • Advanced knowledge of secure software application development and technical processes with considerable in-depth knowledge in one or more technical disciplines (e.g., cloud, artificial intelligence, machine learning, mobile, etc.)
  • Demonstrated experience using enterprise-authorized AI capabilities within the work environment to support security engineering workflows with strong validation habits and awareness of data sensitivity
  • Ability to review and validate AI-assisted code/security recommendations before adoption, escalating uncertainty and ensuring outcomes align to security, resiliency, and auditability expectations

Other signals

  • AI-assisted practices within SDLC/toolchain routines
  • Uses enterprise-authorized AI capabilities within the work environment to accelerate threat modeling, vulnerability analysis synthesis, and security documentation
  • Ability to review and validate AI-assisted code/security recommendations