Manager Information Security

DXC Technology Company; Washington (District of Columbia); In loco; USD 140.000 - 210.000; Tempo pieno

Descrizione del lavoro

DXC Technology is seeking an AI Security Engineer to design, build, and operate AI-enabled security solutions. You will automate vulnerability triage, cloud security posture, DevSecOps, and risk management across DXC’s global environment, turning manual processes into production-grade, measurable systems.

You’ll prototype rapidly with AI-assisted tools, integrate scanners and SIEM/SOAR platforms, and deliver dashboards and audit-ready documentation for leadership and operational teams.

Competenze

• Bachelor’s degree in computer science, information systems, engineering, or equivalent experience.
• Minimum of 3 years of experience in security engineering, security automation, DevSecOps, or security-focused software engineering.
• Experience building automation or tooling in production use, ideally security context.
• Hands-on with vulnerability management platforms, cloud posture management tools, or SIEM/SOAR tooling.

Mansioni

• Design, build, and maintain AI-enabled security solutions that automate vulnerability triage, enrichment, prioritization, and ticket routing.
• Prototype security tools rapidly with AI-assisted development, then harden them for production use.
• Build automation workflows and integrations across scanners, cloud control planes, CI/CD pipelines, Azure DevOps, and SIEM/SOAR platforms.
• Develop cloud security posture management capabilities, including automated misconfiguration detection and drift remediation.
• Embed security into DevSecOps pipelines with automated SAST, DAST, SCA, secrets detection, container and IaC scanning.
• Engineer AI solutions for risk management, such as evidence collection and risk register enrichment.
• Build security dashboards and metrics pipelines for leadership and practitioners.
• Design human-in-the-loop controls, approval gates, and audit logging for automated actions.
• Evaluate and validate AI models, agents, and tools for accuracy, cost, and limitations.
• Produce technical documentation, runbooks, and knowledge articles for operations.

Conoscenze

AI-assisted coding tools

REST APIs / webhooks

Cloud security posture management

Azure DevOps / GitHub Actions

DevSecOps tooling

Vulnerability management

Dashboards / Power BI

Formazione

Bachelor's degree in Computer Science or related

Strumenti

Azure DevOps

GitHub Actions

GitLab

Power BI

Kusto (KQL)

SAST/DAST/SCA tooling

SIEM/SOAR platforms

Descrizione del lavoro

Job Description Summary : DXC’s Global Cyber Security team is building AI-enabled security capabilities that make our risk management faster, more consistent, and more scalable. AI Security Engineers design, build, and operate the solutions that power vulnerability management, cloud security posture management, DevSecOps, risk management, and security metrics across DXC’s global environment. You will combine security domain knowledge with software engineering and AI to turn manual security processes into automated, reliable, and measurable systems. You will work closely with the Vulnerability Management Lead, Data Protection Manager, security architects, risk analysts, cloud and platform engineers, and application development teams. The role suits a builder who is comfortable working in code, prototyping quickly with AI-assisted development tools, and taking solutions from proof of concept to production.

Roles and Responsibilities

• Design, build, and maintain AI-enabled security solutions that automate vulnerability triage, enrichment, prioritization, and ticket routing.
• Use AI-assisted development (“vibe coding”) and modern engineering practices to rapidly prototype security tools, then harden them for production use.
• Build automation workflows and integrations across scanners, cloud control planes, CI/CD pipelines, ticketing systems such as Azure DevOps, and SIEM and SOAR platforms.
• Develop cloud security posture management capabilities, including automated misconfiguration detection, policy-as-code, drift remediation, and guardrails for multi-cloud environments.
• Embed security into DevSecOps pipelines through automated SAST, DAST, SCA, secrets detection, container and infrastructure-as-code scanning, and AI-assisted code review and fix suggestions.
• Engineer AI solutions for risk management, such as evidence collection, control testing, risk register enrichment, and automated assessment support.
• Build security dashboards and metrics pipelines that give leadership and practitioners accurate, timely views of posture, backlog, remediation performance, and risk trends.
• Design human-in-the-loop controls, approval gates, and audit logging for automated and AI-driven actions, so that automation is safe, governed, and explainable.
• Evaluate and validate AI models, agents, and tools for accuracy, false-positive rates, cost, and security, and document their limitations.
• Apply secure coding and engineering practices to security tooling itself, including secrets management, least-privilege access, dependency hygiene, and testing.
• Produce clear technical documentation, runbooks, and knowledge articles so that solutions can be operated and handed off reliably.
• Partner with the security operations, governance, and IT teams to identify manual processes that are good candidates for automation and deliver them iteratively.

Skills and Attributes for Success

• Practical experience using AI-assisted coding tools and LLM APIs, with an understanding of prompt design, evaluation, and the limits of model output.
• Experience building API integrations and event-driven automation, including REST APIs, webhooks, and message queues.
• Working knowledge of cloud security posture management and cloud platforms, particularly Azure and Microsoft 365, with exposure to AWS or GCP.
• Familiarity with DevSecOps tooling and CI/CD platforms such as Azure DevOps, GitHub Actions, or GitLab.
• Understanding of vulnerability management, threat intelligence, and risk frameworks such as NIST CSF, NIST AI RMF, and CIS Benchmarks.
• Ability to design dashboards and metrics using tools such as Power BI, Kusto (KQL), or similar platforms.
• Strong problem-solving skills, a bias toward action, and comfort turning ambiguous security problems into working solutions.
• Clear communication skills, with the ability to explain technical designs to both engineers and non-technical stakeholders.

Requirements

• Bachelor’s degree in computer science, Information Systems, Engineering, or a similar discipline, or equivalent experience.
• Minimum of 3 years of experience in security engineering, security automation, DevSecOps, or software engineering with a security focus.
• Demonstrated experience building automation or tooling that is in production use, ideally in a security context.
• Hands‑on experience with at least one of: vulnerability management platforms, cloud security posture management tools, SAST/DAST/SCA tooling, or SIEM/SOAR platforms.
• Experience with Microsoft Defender for Cloud, Microsoft Sentinel, Microsoft Defender for Endpoint, or equivalent platforms.
• Familiarity with Azure DevOps and Git-based version control workflows.
• Experience with AI or LLM application development, including retrieval-augmented generation, agent frameworks, or evaluation of model outputs, is strongly preferred.