Note: The job is a remote job and is open to candidates in USA. Highmark Health is a leading health and insurance organization seeking a Senior Security Engineer to join its Enterprise Application Security team. The role focuses on embedding shift-left security throughout the software development lifecycle, managing application security tooling, reducing vulnerability risk, supporting secure AI development, enabling developers, and improving enterprise security governance and metrics.
Responsibilities
- Design and implement security guardrails that catch vulnerabilities at the earliest possible point in the development process, including within AI-assisted development workflows, IDEs, at commit time, and within CI/CD pipelines
- Configure and enforce pipeline security gates across the enterprise, ensuring code, AI-generated code, infrastructure-as-code, and deployment artifacts cannot advance to production without meeting defined security standards
- Deploy and manage application security scanners, including SAST, Dependency Scanning, Container Scanning, Secret Detection, DAST, API Security Testing, and emerging AI/LLM security assessment capabilities across the enterprise development platform
- Develop security-as-code policies and enforcement rules that scale across a large, distributed engineering organization
- Partner with Software Delivery Enablement teams to establish security controls, governance requirements, and safe usage patterns for AI coding assistants, AI agents, and AI-enabled developer tooling
- Lead risk-based triage and prioritization of detected vulnerabilities, leveraging exploitability signals such as EPSS scores, Known Exploited Vulnerability (KEV) status, reachability analysis, and emerging AI-specific risk indicators
- Establish and track remediation SLAs aligned to vulnerability severity and business risk, with a focus on eliminating Critical and High findings before they reach production
- Identify and remediate security risks associated with AI-generated code, AI-enabled applications, model integrations, prompt injection vulnerabilities, insecure agent behaviors, and exposure of sensitive data to AI platforms
- Conduct root cause analysis on recurring vulnerability patterns and drive systemic improvements through tooling, standards, secure development practices, and developer education
- Monitor and report on key security health metrics including Mean Time to Remediate (MTTR), security debt trends, pre- versus post-production detection rates, and AI security risk reduction metrics
- Architect and maintain the enterprise application security toolchain, ensuring tools are properly integrated, tuned, and delivering high-fidelity, actionable signal
- Evaluate, onboard, and operationalize emerging security technologies that improve visibility and governance over AI-assisted software development and software supply chains
- Build automation workflows for vulnerability triage, escalation, assignment, and reporting, reducing manual overhead and accelerating response times
- Continuously optimize scanner configurations to minimize false positives and maximize detection accuracy
- Develop dashboards and reporting pipelines that give engineering and security leadership real-time visibility into application security posture, AI security adoption, and policy compliance
- Integrate security controls and monitoring into approved AI development platforms, coding assistants, model gateways, and agentic development workflows
- Serve as a trusted, embedded security advisor to engineering teams, providing hands-on guidance, code review support, AI security consultation, and practical remediation recommendations
- Design and deliver security training, workshops, and reference materials that make secure coding, secure AI development, and responsible use of AI coding assistants accessible and actionable for developers at all levels
- Build and grow a Security Champions program, embedding security advocates within engineering teams to extend the AppSec program's reach across the organization
- Create and maintain secure coding standards, secure AI development standards, design patterns, and reusable security libraries that reduce security burden on development teams
- Develop guidance and reference architectures for secure implementation of LLMs, AI copilots, agentic workflows, model integrations, and AI-enabled business applications
- Partner with development, architecture, and platform teams to embed secure-by-default AI development practices throughout the SDLC
- Define, track, and report on AppSec KPIs that demonstrate program effectiveness and drive continuous improvement
- Establish and report on AI security metrics such as AI tooling adoption, policy compliance, AI risk assessments completed, AI-generated code review coverage, and identified AI-related security findings
- Conduct regular security posture reviews and present findings, trends, and recommendations to engineering and security leadership
- Support audit, risk, and compliance activities by ensuring security controls, AI governance requirements, and secure development standards are documented, measurable, and consistently enforced
- Benchmark program maturity against industry frameworks such as OWASP SAMM, BSIMM, OWASP Top 10 for LLM Applications, and emerging AI security best practices, driving year-over-year improvement
- Continuously assess emerging threats, vulnerabilities, and attack techniques affecting modern software delivery pipelines, software supply chains, and AI-enabled applications
- Assist with security reviews and threat modeling for AI-enabled applications, LLM integrations, AI agents, and AI-assisted development platforms
- Collaborate with Security Architecture to recommend and establish technical controls and guardrails supporting enterprise AI governance requirements
- Evaluate security risks associated with AI models, prompts, training data, model supply chains, MCP integrations, and agentic workflows
- Partner with Architecture, ISRM, and Software Delivery Enablement teams to define secure AI development standards and implementation patterns across the enterprise
- Lead teams in clearly defining requirements, deliverables and timeframes. Escalate issues and make recommendations to resolve them to the appropriate audience
- Conduct root cause analysis to identify and resolve complex problems impacting ISRM Infrastructure
- Develop and/or deliver technical training in complex technical areas. Mentor less senior staff in the execution of their duties
- Complete project tasks to enable the on time, within budget and scope delivery of ISRM Infrastructure projects
- Implement, monitor, configure, and maintain security systems
- Assure compliance to required standards, procedures, guidelines and processes
- Other duties as assigned or requested
Skills
- ***CANDIDATE MUST BE US Citizen (due to contractual/access requirements)***
- * Bachelor's Degree in Computer Science, Information Systems, or closely related field
- * 7 years with Information Security and Systems Analysis
- * 7 years with Information Security and/or Information Risk Management and/or Information Technology
- * 7 years with Operating Systems and Software Administration
- * 7 years developing, communicating and presenting Information Security and Risk Management concepts to varying audiences
- * 7 years with technologies such as Intrusion Prevention Systems (IPS), firewalls, endpoint protection, web/email filtering, Data Loss Prevention (DLP), digital rights management, encryption, Security Event and Incident Management (SEIM), and virtualization platforms
- * Knowledge of HITRUST CSF, NIST 800-83 cyber security framework, PCI, HIPAA, HITECH, COBIT, ISO 27001/2, and ITIL 3
- * Familiarity with secure SDLC best practices
- * Knowledge of Microsoft Apps and Suites, Windows server, SharePoint, etc
- * Strong teamwork and inter-personal skills
- * Hands-on experience with CI/CD platforms such as **GitLab, GitHub Actions, Jenkins**, or equivalent, including security policy enforcement and pipeline governance
- * Proficiency in at least one scripting or programming language (**Python, Go, Bash**, or equivalent) for security automation, workflow development, and security tooling integrations
- * Familiarity with container and cloud-native security concepts including **Docker, Kubernetes, cloud provider security services**, and modern platform engineering practices
- * Ability to conduct focused secure code reviews and security architecture reviews across both human-authored and AI-generated code
- * Experience evaluating security implications of AI coding assistants, AI agents, MCP-enabled tooling, and AI-powered developer platforms
- * Understanding of secure AI development principles, including governance controls for AI-generated code, model consumption, prompt handling, data protection, and human review requirements
- * Preparing and delivering regular security posture briefings to engineering and security leadership, including trend analysis, KPI performance, risk summaries, AI security metrics, and forward-looking recommendations
- * Configuring and managing SCA tools (GitLab Dependency Scanning, OWASP Dependency-Check, JFrog Xray, or equivalent) across multiple package ecosystems
- * Generating, maintaining, and interpreting Software Bills of Materials (SBOMs) in CycloneDX or SPDX formats
- * Applying container security best practices including minimal base images, non-root execution, read-only filesystems, image signing, and software supply chain verification
- * Designing security gates that prevent non-compliant code, dependencies, containers, or deployment artifacts from advancing through the pipeline while minimizing developer friction (GitLab, JFrog Xray, or equivalent)
- * Experience implementing or supporting software supply chain security controls including artifact governance, package repository management, dependency trust validation, and build integrity protections
- * Knowledge of industry frameworks and guidance related to AI and application security, including **OWASP Top 10 for LLM Applications, OWASP SAMM, BSIMM, NIST Secure Software Development Framework (SSDF), and NIST AI Risk Management Framework (AI RMF)**
- * Ability to partner with Architecture, Software Delivery Enablement, Engineering, and Risk Management teams to define and operationalize secure AI development standards and guardrails
- * None
- * None
- 0% - 25%
- * Experience with **GitLab Ultimate security features** including Vulnerability Reports, Security Policies, Compliance Frameworks, and security controls supporting AI-assisted development workflows
- * **Deep proficiency with application security scanning tools** including **SAST, DAST, SCA/Dependency Scanning, Container Scanning, Secret Detection, API Security Testing**, and emerging **AI application security assessment capabilities.**
- * **Deep proficiency with JFrog security and compliance tools** such as **Xray and Curation**, including Policies, Watches, Impact Analysis, Software Supply Chain controls, and reporting
- * Familiarity with **threat modeling methodologies** such as **STRIDE, PASTA**, and their application to **AI-enabled systems, LLM integrations, and agentic workflows.**
- * Working knowledge of common **AI security risks** including **prompt injection, insecure output handling, excessive agency, retrieval risks, model poisoning, training data exposure, sensitive data leakage, and model supply chain threats.**
- * Experience designing or reviewing **security controls for AI-enabled applications, AI assistants, AI agents, or LLM integrations.**
- * Knowledge of healthcare or financial services regulatory frameworks including **HIPAA, PCI-DSS, SOC 2, NIST CSF, NIST AI RMF**, or equivalent governance frameworks
- * Industry certifications such as **CSSLP, GWEB, GWAPT, OSCP, AI Security certifications**, or equivalent
- * **Prior experience as a software developer.** We strongly value candidates who understand what it's like to be on the other side of a security finding and can balance security, delivery, and developer experience
- * Experience coordinating or conducting **penetration testing, red team exercises, AI security assessments, and application threat modeling engagements.**
- * Experience establishing security controls and governance requirements for **AI-assisted software development platforms** (e.g., GitLab Duo, GitHub Copilot, Claude Code, Cursor, MCP-based tooling, or equivalent) within a large enterprise environment
- * Master's Degree in Computer Science, Information Security or related field
- * 10 years with Information Security and Systems Analysis
- * 7 years in IT / Information Security Risk advisory
- * 7 years in-depth understanding of network security architecture, network and networking protocols
- * 7 in Database Management, System Administration and Software Development Life-Cycle
- * 3 years working within an information security function using the HITRUST Common Security Framework (HITRUST CSF), or the NIST 800-83 cyber security framework
- * Certified Information Systems Security Professional (CISSP), Security +
Company Overview