Security Engineer

• Lead security reviews for web applications, APIs, microservices, AWS workloads, internal platforms and AI-enabled products.

• Perform advanced application security testing using SAST, DAST, SCA, manual code review, API testing and business logic testing.

• Identify vulnerabilities across authentication, authorization, session management, access control, injection, SSRF, deserialization, insecure file handling, data exposure and insecure API design.

• Conduct threat modeling for new products, critical features, AWS architectures, AI workflows, identity systems and high-risk data flows.

• Build and improve secure SDLC processes, including security requirements, code scanning, dependency review, CI/CD security gates and release risk assessments.

• Review infrastructure-as-code templates such as Terraform, CloudFormation, AWS CDK, Helm charts and Kubernetes manifests for security misconfigurations.

• Assess AWS environments for IAM weaknesses, exposed services, insecure networking, public S3 buckets, secrets leakage, logging gaps, encryption issues, workload risks and privilege escalation paths.

• Review AWS IAM policies, roles, trust relationships, permission boundaries, service control policies, identity federation and cross-account access patterns.

• Assess AWS services such as EC2, S3, Lambda, ECS, EKS, RDS, API Gateway, CloudFront, WAF, KMS, Secrets Manager, Systems Manager, ECR, VPC, Route 53 and IAM Identity Center.

• Conduct red team exercises, adversary simulations, attack path analysis and controlled exploitation to validate real-world risk.

• Develop proof-of-concept exploits, custom scripts and automation to reproduce vulnerabilities and demonstrate business impact.

• Evaluate containerized and Kubernetes environments, including EKS, for workload isolation, RBAC issues, exposed services, image risks, secrets handling and runtime security gaps.

• Assess CI/CD pipelines for insecure workflows, overprivileged tokens, secrets exposure, supply chain risks, artifact integrity and deployment abuse paths.

• Perform software composition analysis to identify vulnerable dependencies, license risks, malicious packages, transitive dependency exposure and supply chain weaknesses.

• Use SIEM and security telemetry to support investigations, validate attack paths, improve detections and measure control effectiveness.

• Build detection logic, threat hunting queries, dashboards and alerting workflows using SIEM platforms such as Splunk, Microsoft Sentinel, Elastic, Chronicle or AWS-native telemetry.

• Use AWS security services such as GuardDuty, Security Hub, CloudTrail, AWS Config, Inspector, Detective, Macie, IAM Access Analyzer, Security Lake and CloudWatch to improve visibility and detection coverage.

• Automate security workflows using Python, Bash, PowerShell, Go or similar scripting languages.

• Develop threat automation for vulnerability enrichment, alert triage, AWS posture checks, attack simulation, evidence collection and remediation tracking.

• Partner with DevOps and platform teams to improve secrets management, identity controls, network segmentation, logging, monitoring and secure deployment patterns.

• Assess AI and LLM-based systems for risks such as prompt injection, indirect prompt injection, data leakage, insecure tool use, excessive agency, jailbreaks, model abuse, retrieval poisoning and unsafe agent behavior.

• Review AI workloads using AWS services such as Amazon Bedrock, SageMaker, Lambda, API Gateway, S3, KMS and IAM for secure design, data protection and access control.

• Produce clear technical reports with evidence, exploitability, impact, likelihood, risk rating and actionable remediation guidance.

• Mentor engineers and security team members on secure coding, AWS security, offensive testing, threat modeling and AI security risks.

• Strong hands-on experience in application security, product security, AWS cloud security, offensive security or security engineering.

• Deep understanding of secure SDLC practices and experience embedding security into engineering workflows.

• Practical experience with SAST, DAST, SCA, manual penetration testing, code review and vulnerability validation.

• Strong knowledge of OWASP Top 10, OWASP API Security Top 10, OWASP ASVS, common CWE classes and real-world application attack techniques.

• Experience testing web applications, APIs, microservices, cloud services, containers and distributed systems.

• Strong understanding of authentication, authorization, identity federation, OAuth, OIDC, SAML, JWT, session security and access control design.

• Hands-on experience securing AWS environments in production.

• Strong knowledge of AWS IAM, VPC networking, encryption, KMS, Secrets Manager, S3 security, CloudTrail, GuardDuty, Security Hub, AWS Config and workload hardening.

• Experience reviewing infrastructure-as-code and identifying security issues in Terraform, CloudFormation, AWS CDK, Kubernetes YAML, Helm, Dockerfiles or similar technologies.

• Experience with CI/CD security across tools such as bitbucket pipelines, Jenkins, AWS CodePipeline, or similar platforms.

• Experience with red teaming, adversary emulation, penetration testing, exploit development, attack path mapping or offensive security assessments.

• Familiarity with SIEM platforms and the ability to write detection or hunting queries using SPL, KQL, SQL, Lucene, YARA, Sigma or similar languages.

• Strong scripting ability in Python, Bash, PowerShell, JavaScript or similar languages.

• Ability to automate repetitive security tasks and build internal tools that improve security testing, visibility and response.

• Familiarity with container and Kubernetes security, including ECS,EKS, RBAC, admission controls, image scanning, runtime controls, network policies and secrets handling.

• Ability to review code in languages such as Python, JavaScript, TypeScript, Java, Go, Kotlin, C# or similar.

• Strong written and verbal communication skills, with the ability to explain complex technical risks to engineering and leadership teams.

• Experience securing AI-enabled applications, LLM products, autonomous agents, RAG pipelines, AI plugins or ML infrastructure.

• Experience performing AI red teaming, prompt injection testing, jailbreak testing, model abuse testing or evaluation of agentic workflows.

• Experience with AWS Organizations, Control Tower, service control policies, multi-account security patterns and centralized logging.

• Experience with threat modeling methodologies such as STRIDE, PASTA, attack trees, abuse cases, data flow diagrams or architecture risk reviews.

• Experience with security automation, SOAR workflows, detection-as-code, policy-as-code or cloud security posture automation.

• Experience with tools such as Burp Suite Pro, OWASP ZAP, Semgrep, CodeQL, Checkmarx, Fortify, Veracode, Snyk, Dependabot, Trivy, Grype, Syft, Gitleaks, Checkov, tfsec, Prowler, ScoutSuite, Wiz, Prisma Cloud or similar.

• Experience building custom security tooling, scanners, exploit harnesses, detection rules, cloud guardrails or CI/CD security integrations.

• Experience with MITRE ATT&CK, MITRE ATLAS, CIS Benchmarks, AWS Well-Architected Security Pillar, NIST, ISO 27001, SOC 2, PCI DSS or similar frameworks.

• Experience with bug bounty programs, coordinated vulnerability disclosure, internal red team programs or external penetration testing engagements.

• Relevant certifications such as OSCP, OSWE, OSEP, GWAPT, AWS Certified Security Specialty, AWS Solutions Architect, CISSP or equivalent practical experience.

• Security is embedded into design, development, testing and deployment workflows.

• SAST, DAST, SCA, secrets scanning, IaC scanning and AWS posture checks are implemented with practical tuning and low operational noise.

• High-risk application and AWS vulnerabilities are identified early, validated accurately and remediated with engineering partnership.

• Threat models are used to influence architecture decisions before systems reach production.

• Red team findings translate into improved controls, stronger detections and reduced attack paths.

• SIEM, AWS logs and security telemetry are used to validate security controls and detect realistic abuse scenarios.

• Security automation reduces manual review effort and accelerates vulnerability management, investigation and remediation.

• AI-enabled systems are reviewed for emerging threats before they are released or scaled.

• Engineering teams view security as a technical partner that helps them ship resilient products.