Cybersecurity Engineer – Engineering

Keep security policies and technical documentation accurate as systems change.

Embed security checks into CI/CD (GitHub Actions) so issues surface at pull-request time. Write Python and shell automation for evidence collection, configuration auditing, and remediation.

Build tooling and guardrails that make the secure path the easy path for engineers. Improve identity and access management across cloud, SaaS, and internal tooling.

Partner with engineering, DevOps, and product teams as an embedded security reviewer. Run practical security training and awareness for engineering.

Communicate risk clearly to both technical and non-technical audiences, with a recommendation attached.

Use modern AI tools to accelerate code review, detection engineering, and analysis.

Apply AI-assisted practices while maintaining rigorous verification, data-handling, and review standards.

Assess and secure the organization’s own use of AI services, including data-exposure risk.

Bachelor’s or Master’s degree in Computer Science, Information Security, or a related discipline. 6+ years in cybersecurity, with substantial application security or cloud security ownership. Strong AWS security experience — IAM, VPC networking, encryption, logging, and common misconfiguration patterns.

Ability to read and reason about production code; Python strongly preferred, plus JavaScript/TypeScript.

Hands-on web application and API security testing (OWASP Top 10, OWASP API Security Top 10) using black-box, grey-box, and white-box approaches.

Ability to write up findings with reproducible steps, impact, severity rationale, and a concrete remediation path.

Practical experience with SAST/DAST/SCA and container scanning tooling, including triage and remediation.

Working knowledge of Docker and container orchestration (ECS/Fargate or EKS). Experience with vulnerability management and incident response in production environments. Familiarity with HIPAA, SOC 2, or equivalent compliance frameworks.

Solid Linux fundamentals, networking, and cryptography basics.

Clear written and verbal English; ability to document findings and risk decisions precisely.

Secure Code Review (Python / Django / FastAPI, Node.js, React / TypeScript) Threat Modeling (STRIDE or equivalent)

OWASP Top 10 / OWASP API Security Top 10

Authentication, Authorization, Multi-Tenant Isolation

Black-Box / Grey-Box / White-Box Penetration Testing

Manual Exploitation and Proof-of-Concept Development

SAST / DAST / SCA, Secret and Dependency Scanning

Burp Suite, OWASP ZAP, Semgrep, Trivy, and similar tooling

AWS IAM, VPC, Security Groups, KMS, GuardDuty, Security Hub, CloudTrail, Config ECS / Fargate / EKS Workload Security

Terraform Security Review, Policy as Code (OPA, Checkov, tfsec)

Secrets Management (AWS Secrets Manager, SOPS, Vault)

Network Segmentation and Perimeter Controls

SIEM / Log Analytics and Detection Engineering

Incident Response and Digital Forensics

Vulnerability Management and Risk-Based Prioritization

Audit Logging, Access Review, Monitoring and Alerting

Encryption at Rest and in Transit, Key Management

PHI / PII Handling, Data Classification, Retention

HIPAA, SOC 2, HITRUST, NIST CSF, ISO 27001

Vendor and Third-Party Risk Assessment

PostgreSQL Security and Access Control

Kafka / Redpanda / Amazon MSK, Redis

GitHub Actions and CI/CD Security

Python and Shell Automation

Security certifications — OSCP, CISSP, AWS Security Specialty, GIAC (GWAPT, GCIH, GCSA), or CEH.

Experience securing multi-tenant SaaS platforms and tenant-isolation models. Prior experience carrying a SOC 2 Type II audit or HIPAA program through to completion. Offensive security background — black-box penetration testing, red teaming, or bug bounty experience.

Experience scoping and managing third-party black-box or grey-box penetration tests. Kubernetes security.

Experience with event-driven architectures and message-broker security.

Detection-as-code and security automation at scale.

Exposure to healthcare technology or other regulated domains.

Experience securing AI/LLM-integrated applications.

Genuine hands-on depth — you find real issues, not just scanner output.

Engineering mindset: you fix and automate rather than only report.

Sound risk judgment and the ability to prioritize what actually matters.

Strong collaboration; engineers should want your review, not dread it.

Precise written communication and clean documentation.

Integrity, discretion, and ownership when handling sensitive data.

Continuous learning as the threat landscape moves.

Security ownership of a healthcare platform where the stakes are real.

Breadth across application, cloud, and operational security in one role.

Modern stack: AWS, Terraform, GitHub Actions, Docker, Python, React, PostgreSQL, Kafka compatible messaging.

Direct influence on architecture and engineering practice, not a downstream audit function.