Key ResponsibilitiesSecurity Control Engineering

- Deploy, configure, and maintain core security platforms including EDR, email, service edge, cloud security posture management, and identity controls.

- Design control rollouts that account for coverage gaps, exception handling, impact, and rollback.

- Integrate security tooling with IT and engineering systems so data flows are usable, not just collected.

- Own control health monitoring: agent coverage, policy failed enforcement, and failure detection.

Cloud and Infrastructure Security

- Implement and maintain guardrails across AWS, Azure, and GCP, including preventative posture monitoring, and remediation workflows.

- Build and maintain hardened baselines for operating systems, containers, and cloud services aligned to CIS or equivalent benchmarks.

- Engineer secrets management, key management, and certificate lifecycle controls in partnership with platform teams.

- Support secure network design implementation including segmentation, egress control, and remote access.

Automation and Engineering Practice

- Automate repetitive security operations work through scripting, APIs, and code.

- Treat security configuration as code: version control, peer review, testing, and repeatable infrastructure as code deployment.

- Build and maintain integrations between security, IT, and engineering systems so data flows without manual handling.

- Write and maintain documentation and runbooks valuable enough that someone else can operate what you built.

Operations Support and Remediation

- Support incident response with rapid control changes, containment actions, and forensic data collection.





- Partner with Vulnerability Management to isolate root causes for vulnerabilities, automated incident triage, and investigation ticket.

- Participate in an on-call rotation for security platform issues and high-severity incidents.

- Contribute to control evidence collection for audit and customer assurance activity.

AI/ML Security

- Implement security guardrails for internal AI/LLM systems, including protections against prompt injection, model poisoning, and unauthorized data exfiltration.

- Maintain and secure the enterprise AI infrastructure, ensuring secure configuration of AI and model serving environments.

- Monitor and audit AI usage, ensuring adherence to governance policies for non-human identities and autonomous agents.

- Stay current on emerging threats to AI systems and adapt security controls to defend against AI-assisted attack vectors.

Required Qualifications

- Experience: 5+ years in security engineering, infrastructure engineering with a security focus, or a closely related hands-on role.

- Platform Ownership: Demonstrated ownership of at least two enterprise security platforms end to end, including deployment, tuning, and ongoing operation.

- Cloud Expertise: Strong cloud security engineering experience with at least one major provider, including native security services and policy enforcement.

- Automation: Practical scripting and automation skills working against vendor APIs.

- Core Systems: Solid grounding in operating system internals, networking, and identity protocols such as SAML, OIDC, and OAuth.

- Practices: Experience supporting infrastructure as code and version-control workflows.

- Problem Solving: Troubleshooting discipline able to isolate root causes in complex environments without guessing.

📌 Security Control Engineering (Bengaluru)
🏢 HCLTech
📍 Bengaluru