Cybersecurity Engineer

About LockedIn AI
LockedIn AI is the #1 real-time AI interview and meeting copilot, trusted by over 1 million users worldwide. We are building a next-generation AI-powered career preparation platform that helps users perform confidently in live job interviews, coding assessments, and professional meetings.

Our system operates at scale, powering real-time AI assistance across multiple products. Security is not optional—it is foundational.

Role Overview
We are hiring a Cybersecurity Engineer to design, build, and operate the security systems that protect LockedIn AI’s cloud infrastructure, applications, APIs, AI models, and user data.

This is a hands-on engineering role, not a policy-only position. You will actively build security tools, harden infrastructure, detect threats, and respond to incidents across systems used by over 1 million users.

You will work across cloud infrastructure, application security, AI systems, and DevSecOps pipelines to ensure the platform is secure by design and resilient at scale.

Key Responsibilities
Security Architecture & Engineering
Design secure cloud and application architectures across AWS/GCP/Azure
Implement zero-trust, least-privilege, and defense-in-depth models
Build and maintain security systems including WAFs, IDS/IPS, and network segmentation Manage IAM systems, authentication flows, MFA, and privileged access controls

Vulnerability Management & Testing
Conduct vulnerability assessments and penetration testing across systems
Identify and remediate security flaws in applications, APIs, and infrastructure
Perform secure code reviews and threat modeling for new features
Manage full vulnerability lifecycle from discovery to resolution

Cloud & Infrastructure Security
Harden cloud environments and Kubernetes clusters
Secure Docker containers, images, and runtime environments
Implement CSPM and infrastructure compliance monitoring
Manage secrets, keys, and certificate lifecycle securely

Security Monitoring & Incident Response
Build SIEM systems, logging pipelines, and anomaly detection
Monitor real-time security events and investigate incidents
Lead incident response, containment, and postmortems
Create detection rules for malicious activity and system abuse

AI System Security
Secure LLM APIs, AI pipelines, embeddings, and model endpoints
Prevent prompt injection, model extraction, and data leakage attacks
Monitor AI systems for abnormal behavior and adversarial usage
Protect training data, inference systems, and vector databases

Compliance & Governance
Support SOC 2, ISO 27001, GDPR, and CCPA readiness
Maintain security documentation, policies, and audit trails
Conduct security awareness training across engineering teams

Required Qualifications
3+ years in cybersecurity engineering, DevSecOps, or application security
Experience securing cloud-native systems and production environments

Hands-on expertise with AWS, GCP, or Azure security
Strong knowledge of Docker, Kubernetes, and container security
Experience with SIEM tools, vulnerability scanners, and security pipelines
Proficiency in Python, Bash, or Go for automation and tooling
Understanding of IAM, encryption, networking, and system hardening