Open to opportunities

Prarthana MaddurRamesh

@prarthanamaddurrames

Message

I am a cloud security engineer specializing in IAM, threat detection, and cloud incident response.

United States

Message

What I'm looking for

I seek a mid-level cloud security role focused on IAM, incident response, threat hunting, and security automation in a collaborative, growth-oriented team using AWS/Azure.

I am a cloud security engineer and cybersecurity analyst with over three years of hands-on experience securing enterprise cloud environments across AWS and Azure, with deep expertise in IAM, EDR, SIEM, and vulnerability management.

At IBM I designed and implemented IAM strategies using AWS IAM and AWS SSO, led penetration testing and vulnerability assessments that reduced the attack surface by 35%, detected and mitigated 500+ cloud threats reducing MTTR by 30%, automated patch management across 5,000+ AWS instances, and deployed Delinea PAM to secure 1,000+ critical accounts.

I am passionate about proactive threat hunting, security automation, and aligning controls with ISO 27001, NIST, and SOC 2 to improve audit readiness and overall security maturity, and I strive to strengthen enterprise defenses through measurable improvements and training.

Experience

Work history, roles, and key accomplishments

Current

CyberSecurity Analyst

Current

IBM

Mar 2024 - Present (1 year 5 months)

Designed and implemented IAM strategies and automated threat detection across AWS, conducting penetration testing and incident response that detected and mitigated 500+ cloud threats and reduced MTTR by 30%. Hardened EC2/RDS and automated patching to achieve 100% high-severity coverage while reducing misconfigurations by 35% and improving audit readiness by 30%.

AWS IAM Incident Response Penetration Testing Cisco Umbrella SIEM Security Automation

CyberSecurity Analyst

McAfeeby Nefroverse

Nov 2020 - Dec 2022 (2 years 1 month)

Engineered secure, scalable AWS environments for financial analytics (500GB+), performing penetration testing and implementing IAM/MFA that improved compliance and reduced unauthorized access. Built ML-based fraud detection and predictive models that improved forecasting accuracy by 25%, reduced false positives by 22%, and optimized data pipelines to speed processing by 35%.