The project is part of a next-generation SaaS technology platform operating in the transportation and supply chain logistics domain. The company behind the platform has decades of industry experience and is recognized as an employer of choice, with a strong culture of innovation and technical excellence.

The platform delivers a suite of data-driven software solutions used daily by millions of customers who rely on accurate, real-time insights to make informed business decisions and improve profitability. At its core, the system supports one of the largest digital marketplaces in its industry, processing hundreds of millions of transactions annually and maintaining a massive database representing hundreds of billions of dollars in global market activity.

The technology stack is built to handle extreme scale, high availability, and data accuracy, enabling customers to operate efficiently in a fast-moving, competitive environment. Engineering teams work on highly distributed systems, advanced data processing pipelines, and analytics-driven services that continuously evolve to meet growing market demands.

Responsibilities:

You will own vulnerability management end to end, and you will design, build and implement:

• Design, build, and mature the enterprise Vulnerability Management Program end to end, covering application/code, endpoint, and infrastructure vulnerabilities within client’s environment.

• Integrate vulnerability data from multiple existing security and engineering tools into unified, owner assigned workflows

• Design and implement the integrations between vulnerability sources, ticketing systems, and other internal platforms yourself, and build the automated workflows for ingestion, processing, assignment, tracking, and reporting rather than only recommending them.

• Build dashboards and reporting that give visibility into outstanding vulnerabilities, ownership, remediation progress, and SLA and policy compliance, broken out by team and by system.

• Define and enforce remediation SLAs benchmarked to industry standards, tightened where needed to keep DAT's response time ahead of adversaries who are increasingly using AI to find and exploit vulnerabilities faster.

• Apply an AI first mindset, actively identifying where AI or GenAI can automate or improve vulnerability management workflows rather than defaulting to a manual process.

• Align the program to NIST CSF (Identify: Risk Assessment, Protect: Platform Security, Detect: Continuous Monitoring) and support evidence needs for DAT’s Security Control Framework and related audits. (e.g., SOC 2, PCI, SOX)

• Partner with Security, Engineering, and IT stakeholders as a collaborator, making remediation practical and sustainable while balancing secure and fast software development.

• Perform security design reviews of HLDs and LLDs, and help product and engineering teams build secure by design.

• Run vulnerability and exposure management workflows: integrate scanner data with ticketing systems, assign owners, and report on remediation SLAs.

• Lead the secrets management modernization: secret scanning and push protection, migration to AWS Secrets Manager, rotation automation, and leak-response runbooks.

Skills Required

• Bachelor's degree in Computer Science, Information Security, Engineering, or a related field, or equivalent practical experience.

• 6-8 years of hands-on experience in vulnerability management or security engineering, with a track record designing, building, or significantly scaling a vulnerability management program.

• Experience of scaling an enterprise VM program end-to-end.

• Working knowledge of vulnerability management across application/code, endpoint, and infrastructure/cloud security, specifically AWS.

• Experience integrating security platforms with ticketing and work management systems.

• Understanding of vulnerability prioritization, ownership, remediation processes, SLAs, and security metrics.

• Familiarity with NIST CSF and security controls, and with SOC 2 expectations for vulnerability management.

• Ability to independently design an end to end technical solution with limited predefined specification.

• Understanding of AI and GenAI capabilities and practical opportunities to apply them to security automation.

• Strong hands-on experience with AWS security: IAM, CloudTrail, GuardDuty, KMS, network controls, and securing EKS or similar workloads.

• Application security experience: SAST and code scanning (CodeQL or similar), secret scanning, dependency scanning, and secure SDLC practices.

• Experience with secrets management: AWS Secrets Manager or HashiCorp Vault, rotation, and leak response.

• Scripting or programming skills (Python preferred) and experience building automation and integrations, including with ticketing systems such as Jira.

• Infrastructure-as-code experience (Terraform or Pulumi) and CI/CD pipelines (GitHub Actions).

• Understanding of vulnerability prioritization, remediation workflows, SLAs, and security metrics.

• Clear written and spoken English, including writing design documents and working with engineering teams.

Preferred

• Experience integrating vulnerability or security programs across organizations involved in M&A activity.

• Direct experience preparing vulnerability management evidence for a SOC 2 Type 2 audit.

• GPEN, OSCP, CEH,  or an equivalent technical certification.

• Experience with SIEM and detection engineering (CrowdStrike Falcon Next-Gen SIEM, detection as code, MITRE ATT&CK).

• Experience with Zero Trust, SSO/MFA and PAM.

• Kubernetes, Helm and GitOps secret handling.

• Direct experience preparing evidence for a SOC 2 Type 2 audit, or familiarity with PCI and SOX.

• Experience integrating security programs across organizations during M&A.

• Experience running a security champions or developer-enablement program.

• A security certification such as GPEN, OSCP, CEH, AWS Security Specialty or CISSP.