AI-Driven App Security Engineer for Health Tech

Tempus AI, Inc.; Chicago (IL); On-site; USD 85,000 - 130,000; Full time

Job summary

Tempus AI, Inc. is seeking an Application Security Engineer to secure software from design through release.

You will partner with product and engineering to embed security into the SDLC, and assess applications and APIs with attacker perspectives through security assessments and penetration tests. You will own defined security problems, including AI/LLM-enabled features, while coordinating with teams to implement robust controls and guardrails.

Qualifications

• 3–5 years of applying security practices in software projects.
• Experience with web apps, APIs, and cloud services using security testing tools.
• Familiarity with AI/LLM-enabled security considerations (prompt injection, data leakage).
• Proficient in at least one security design method (STRIDE/PASTA).

Responsibilities

• Embed security into the SDLC with threat modeling and design reviews.
• Conduct application security assessments and penetration tests; document findings and risks.
• Assess AI/LLM-enabled features, guardrails, and data access controls.
• Integrate SAST, DAST, and SCA into CI/CD pipelines; tune tooling.
• Build secure-by-default patterns and guardrails to prevent vulnerabilities.
• Leverage AI-assisted tooling to scale reviews and remediation.
• Communicate risk to developers and leadership.
• Design and document application security controls and standards.

Skills

Application security

Penetration testing

Web applications

APIs

CI/CD pipelines

Python

Go

JavaScript

Threat modeling

Communication

Tools

Burp Suite

SAST

DAST

SCA tools

CI/CD tooling

Docker

Kubernetes

Job description

Tempus AI, Inc. is seeking an Application Security Engineer to secure software from design through release.

You will partner with product and engineering to embed security into the SDLC, and assess applications and APIs with attacker perspectives through security assessments and penetration tests. You will own defined security problems, including AI/LLM-enabled features, while coordinating with teams to implement robust controls and guardrails.