Sr Security Platform Engineer, AI and Automation
vanguardDallas (TX)
Sr Security Platform Engineer, AI and Automation
Posted today
vanguardDallas (TX)
SENIORITY
Manager
About the role
Overview:
In this role you will design and build secure, cloud-native platform services on AWS to support scalable security testing across Vanguard's SDLC. You will integrate AppSec tooling and AI-enabled capabilities to advise remediation and enforce security controls. You’ll partner with architects and cross-functional teams to evolve the AI Harness and security orchestration platform, delivering reliable, developer-friendly security at scale. This is an opportunity to shape secure software delivery and drive transformation with AI-enabled protection.
Responsibilities:
Lead design, development, and deployment of secure, cloud-native platform services on AWS (IAM, ECS, Lambda, Step Functions, RDS, S3, CloudFormation) Integrate security tools into SDLC pipelines and translate findings into enforceable controls Advance AI scanning capabilities and the AppSec AI Harness from PoC to production Design integration patterns for AI findings ingestion and validation of AI remediation Architect integration of AI capabilities into broader platform architecture and delivery roadmap Serve as SME for AI-enabled application security and practical AI applications in DevSecOps Develop APIs, event-driven integrations, automation services, and CI/CD capabilities for scalable security testing Improve platform reliability and scalability via automation, observability, and self-service features Embed secure development practices across lifecycle (SAST, SCA, container security, API security) Provide technical leadership and mentorship in AI, AppSec, and platform engineering Collaborate with stakeholders to define technical direction, assess risks, and deliver AI-enabled security solutions Coordinate with DevSecOps leadership to align engineering priorities with strategic initiatives Drive continuous improvement across platform architecture, engineering standards, security practices, and operations
Key requirements:
12+ years in software engineering, application development, or platform engineering 8+ years hands-on software development Strong AWS cloud and cloud-native architecture experience Proficiency in Node.js and TypeScript; Python valued for AI/LLM work Hands-on experience building agentic AI solutions Experience integrating LLMs into production apps (prompt design, tool calls, context management, cost/latency considerations) Experience evaluating AI output quality and establishing release criteria Experience designing APIs, distributed systems, automation, and CI/CD pipelines Experience operating production services with observability and reliability practices Proven ability to lead complex technical initiatives and mentor engineers Willingness to learn new technologies as platforms evolve leadership cross-functional collaboration mentorship AWS cloud technologies Cloud-native platform architectures Node.js
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