Arvind Dooda

Cybersecurity Engineer with approximately 4 years of combined professional experience in cloud security, security operations, application security, and AI/LLM security testing. Skilled in securing AWS environments, implementing IAM and Zero Trust controls, conducting vulnerability assessments, and automating threat detection and response using Python, Splunk, and AWS security services. Experienced in supporting NIST-aligned security controls and compliance readiness across healthcare, financial services, and energy environments.

CLOUD SECURITY ENGINEER at ELEVANCE HEALTH (2026-05 – Present)

• Engineered secure AWS multi-account environments supporting 100K+ internal users, implementing security controls aligned with HIPAA, FedRAMP, and HITRUST requirements.
• Refactored GitHub repositories and secrets management configurations, strengthening access controls and reducing security misconfigurations by 70%.
• Integrated Okta SSO/MFA with 10+ enterprise applications, including GitLab, Databricks, and AWS WorkSpaces, securing authentication for 5,000+ users and enforcing role-based access control (RBAC).
• Developed Amazon CloudWatch dashboards and proactive security alerting, reducing incident response time by 35%, while automation-driven optimizations lowered monthly infrastructure costs by 15%.
• Developed Python security automation scripts and AWS Lambda functions to enforce encryption, patch compliance, and Zero Trust security principles across AWS accounts.
• Provisioned and secured 300+ AWS resources using Terraform across VPC, EC2, S3, IAM, and RDS, improving infrastructure provisioning efficiency by 60%.
• Implemented NIST 800-53-aligned security controls, including least-privilege IAM, encryption, centralized logging, and network segmentation across cloud environments.
• Integrated security controls into CI/CD pipelines using Jenkins, GitHub, and Ansible, accelerating release cycles by 40% and reducing manual security validation failures by 90%.
• Collaborated with CloudOps teams on infrastructure monitoring, incident response, and compliance activities supporting mission-critical healthcare systems.
• Supported FedRAMP and HITRUST audit readiness by collaborating with 3PAOs and compliance teams on Plans of Action and Milestones (POA&M), technical control validation, and security documentation.

CYBERSECURITY ENGINEER – AI/Cloud security at LUMENA ENERGY (2025-09 – 2026-05)

• Conducted application, cloud, and AI/LLM security assessments for Diode AI, an internal AI project, using Burp Suite, Nessus, and Python-based testing tools, identifying 15+ security vulnerabilities and supporting remediation.
• Performed adversarial prompt injection and LLM misuse testing to identify security weaknesses in internal AI applications and strengthen AI security controls.
• Applied STRIDE and PASTA threat modeling across AI applications and cloud infrastructure to identify attack vectors, assess security risks, and recommend mitigation strategies.
• Performed secure code reviews of Python and JavaScript applications, identifying security weaknesses and collaborating with development teams to improve secure coding practices.
• Automated vulnerability scanning and assessment workflows using Nessus and Python, improving testing efficiency by 40% across development and production environments.
• Integrated security controls into CI/CD pipelines and developed Python and PowerShell scripts to automate security validation and support secure software delivery.
• Managed PKI/TLS certificate infrastructure and collaborated with engineering teams to secure application communications and cloud-hosted services.
• Collaborated with SOC and compliance teams to support SOC 2 Type II audit readiness through security risk assessments, cloud control validation, and vulnerability remediation tracking across AWS and GCP environments.

CYBERSECURITY ENGINEER at WELLS FARGO (2024-07 – 2025-08)

• Assisted in architecting real-time threat detection pipelines using Splunk and AWS GuardDuty, processing 2M+ security events daily and reducing mean time to detect (MTTD) by 35% and mean time to respond (MTTR) by 20%.
• Engineered security-focused data pipelines using Apache Airflow and AWS Lambda, strengthening cloud monitoring and reducing attack surface by 20% across financial systems processing 5TB+ of transaction data.
• Developed and deployed 30+ Splunk detection rules for advanced persistent threats (APT), phishing, and malware, improving threat detection accuracy and reducing false positives across SOC operations.
• Conducted vulnerability assessments and penetration testing using Burp Suite and Metasploit, supporting remediation of 95% of identified critical production vulnerabilities.
• Automated incident response and security investigation workflows using Python and Bash, reducing manual intervention by 30% while supporting SLA compliance across 200+ daily security alerts and cases.
• Built an enterprise security monitoring platform processing 1M+ logs daily and integrated PagerDuty alerting across 50+ applications, achieving 25% faster response times and cutting average incident response by 90 minutes.
• Automated secure infrastructure provisioning using Terraform and CI/CD pipelines, reducing security vulnerabilities by 15%.
• Implemented NIST 800-53-aligned security controls across 10+ enterprise applications, collaborating with security teams on risk mitigation, security awareness, and operational improvements.

CYBERSECURITY ANALYST at RENAULT NISSAN TECHNOLOGY & BUSINESS CENTRE INDIA (2022-02 – 2023-06)

• Monitored and triaged security alerts in IBM QRadar across EDR, IDS/IPS, email security, and endpoint telemetry, investigating suspicious activity and escalating critical threats through established incident response workflows.
• Investigated 30+ security incidents using IBM QRadar, CrowdStrike, and IDS/IPS telemetry, performing root cause analysis and supporting containment, remediation, and incident documentation.
• Conducted application and network security assessments across 20+ systems using Nmap, Burp Suite, Metasploit, and Nessus, tracking vulnerability remediation through ServiceNow.
• Supported identity and access management (IAM) for 500+ user and service accounts, conducting access reviews, authentication troubleshooting, and security audit documentation.
• Automated threat hunting and log analysis workflows using Python and Bash, improving SIEM alert triage efficiency and accelerating security investigations.
• Analyzed Nessus vulnerability scan results across Linux and Windows environments, prioritizing remediation based on CVSS severity, asset criticality, and NIST risk management principles.

SOFTWARE ENGINEER INTERN at ACCENTURE (2021-06 – 2021-08)

• Assisted in developing machine learning models for credit risk scoring and underwriting using Python and Scikit-learn, improving loan default prediction accuracy by 18%.
• Developed RESTful microservices using Python, FastAPI, and Flask, supporting integration with cloud-hosted fintech and insurance applications.
• Contributed to AI/ML application development using TensorFlow, OpenCV, and Python, supporting model integration and deployment workflows.
• Supported cloud application deployment and CI/CD automation using Microsoft Azure, Docker, GitHub Actions, and Azure DevOps while collaborating with cross-functional Agile teams.

Master of Applied Science in Cybersecurity Engineering – Illinois Institute of Technology (2025-05)

Bachelor of Engineering in Computer Science – Anna University (2023)