Sr Security Platform Engineer, AI and Automation

Vanguard; Charlotte (NC); Sur place; USD 150 000 - 230 000; Plein temps

Résumé du poste

Vanguard’s Global Enterprise Security team seeks a senior engineer to design and scale secure, cloud-native platform services on AWS, integrating SAST/SCA, container security, and AI-driven remediation into development pipelines.

You will lead AI capability design, collaborate with architects, and drive production-ready security tooling that enables developers to ship more secure software at scale.

Qualifications

• 12+ years of experience in software engineering, application development, or platform engineering.
• Undergraduate degree or equivalent combination; graduate degree preferred.
• Strong expertise in AWS cloud technologies and cloud-native architectures.
• Strong software engineering and programming fundamentals in Node.js/TypeScript; Python valuable for AI.
• Hands-on experience building agentic AI solutions in production systems.
• Experience integrating large language models (LLMs) into production apps and prompts.
• Ability to evaluate AI output quality and establish release criteria.
• Experience in secure SDLC integrations (SAST, SCA, container security).

Responsabilités

• Lead design and implementation of secure, cloud-native platform services on AWS.
• Integrate security tools into SDLC pipelines and translate findings into controls.
• Advance AI scanning capabilities and AppSec AI Harness toward production.
• Design AI-security integration patterns and validate AI remediation outputs.
• Align platform engineering with architecture standards and delivery roadmap.
• Provide technical leadership in AI-enabled application security.
• Develop APIs, event-driven integrations, and CI/CD for secure testing.
• Improve reliability and observability of the orchestration platform and AI.
• Promote secure development practices across the lifecycle.

Connaissances

Software engineering

AWS

Node.js

TypeScript

Python

AI integration

Security automation

Mentorship

Formation

Bachelor's degree or higher

Outils

SAST

SCA

CloudFormation

ECS

Lambda

Step Functions

RDS

S3

Description du poste

Global Enterprise Security (GES) partners with the lines of business across Vanguard to protect crew and client information and assets. Our sub-department, Attack Surface Reduction, provides a cohesive view into Vanguard's technical attack surface, focused on identifying, prioritizing, and managing vulnerabilities and configuration issues across the organization.

DevSecOps, part of Attack Surface Reduction, enhances the security posture of Vanguard's software applications through security automation that helps developers find and fix vulnerabilities earlier in the SDLC.

This role sits on the team responsible for orchestration and enforcement of our security scanning capabilities, including SAST, SCA, container scanning, and API security scanning. We build the platform that runs these scans across Vanguard's pipelines and enforces security policies, and we are extending it with AI capabilities that analyze findings and recommend remediation for developers. You will work closely with the engineers within our team, architects, Security Architecture and Engineering (SAEP), AI, Data and Platform Technology (ADAPT), IAM, Technical Security Advisors and teams across Attack Surface Reduction to shape how security testing is delivered at scale.

Responsibilities

• Lead the design, development, and implementation of secure, cloud-native platform services on AWS, leveraging technologies such as IAM, ECS, Lambda, Step Functions, RDS, S3, and CloudFormation.
• Integrate application security tools and scanning capabilities into Software Development Life Cycle (SDLC) pipelines, including onboarding new security scanners, normalizing findings, and translating results into enforceable security controls.
• Partner with tech lead and architects on the technical direction for AI scanning capabilities and the AppSec AI Harness, taking agentic vulnerability analysis and remediation from proof of concept to a supported production capability.
• Design integration patterns between AI capabilities and the security orchestration platform, including ingestion of security findings, validation of AI-generated remediation, and measurement of output quality as models and prompts evolve.
• Partner with technical leads and architects to integrate AI capabilities into the broader platform architecture, engineering standards, and delivery roadmap.
• Serve as a technical subject matter expert for AI-enabled application security, establishing practical approaches for applying AI to security challenges across DevSecOps.
• Design and develop APIs, event-driven integrations, automation services, and CI/CD capabilities that enable reliable, scalable security testing and simplify adoption for development teams.
• Improve the reliability and scalability of the orchestration platform and AI capabilities through automation, observability, and self-service capabilities.
• Collaborate with security and engineering teams to embed secure development practices throughout the development lifecycle, including Static Application Security Testing (SAST), Software Composition Analysis (SCA), container security, and API security testing.
• Provide technical leadership and mentorship, promoting high-quality software engineering practices and strengthening the team's capabilities in AI, application security, and platform engineering.
• Partner with stakeholders to establish technical direction, manage technical risks, and deliver business-critical solutions, including determining where AI provides meaningful value within application security.
• Collaborate with DevSecOps leaders to align engineering priorities and deliverables with strategic initiatives as business and technology needs evolve.
• Drive continuous improvement across platform architecture, engineering standards, security practices, and operational excellence.

Required Qualifications

• 12+ years of experience in software engineering, application development, or platform engineering, including 8+ years of hands-on software development experience.
• Undergraduate degree or an equivalent combination of relevant education, training, and experience; graduate degree preferred.
• Strong expertise in AWS cloud technologies and cloud-native application and platform architectures.
• Strong software engineering and programming fundamentals, with the ability to work effectively across multiple programming languages. Current technologies include Node.js and TypeScript, with Python particularly valuable for AI and large language model development.
• Hands-on experience building agentic AI solutions, including multi-step, tool-using agents integrated into production systems.
• Experience integrating large language models (LLMs) into production applications, including prompt design, tool/function calling, context management, cost optimization, and latency management.
• Practical experience evaluating the quality and reliability of AI-generated output, including establishing release criteria and identifying degradation after deployment.
• Experience desi