Senior Security Platform Engineer, AI and Automation

Vanguard

. Lead the design, development, and implementation of secure, cloud-native platform services on AWS using IAM, ECS, Lambda, Step Functions, RDS, S3, and CloudFormation .

Posted 10/27/2026full-timeUnited StatesSeniorWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in AWS cloud technologies and cloud-native application architectures, with a strong focus on AI-enabled application security and DevSecOps practices. Proven ability to lead technical initiatives, mentor teams, and integrate advanced AI capabilities into secure platform services.

Highest-signal resume keywords

AWS Cloud TechnologiesAI-Enabled Application SecurityNode.js and TypeScript DevelopmentCI/CD Pipeline ImplementationDevSecOps Practices

ATS Keywords

Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills

Software EngineeringApplication DevelopmentPlatform EngineeringAPI Design and DevelopmentAutomation SolutionsDistributed SystemsAI Solutions DevelopmentLarge Language Model IntegrationSecurity TestingObservability and Reliability Engineering

Soft Skills

Technical LeadershipMentorshipCollaborationInfluencing Across BoundariesContinuous Improvement

Tools & Technologies

AWS IAMAWS ECSAWS LambdaAWS Step FunctionsAWS RDSAWS S3AWS CloudFormationSnykWizJFrog Xray

Certifications & Qualifications

AWS Certifications

Industry Keywords

DevSecOpsSecure Software DevelopmentEnterprise AI/Data PlatformsPlatform EngineeringEnterprise-Scale Automation

Tech Stack

Tools & technologies

AWSCloudDistributed SystemsJavaScriptNode.jsPythonSDLCTypeScript

About the role

Key responsibilities & impact

Lead the design, development, and implementation of secure, cloud-native platform services on AWS using IAM, ECS, Lambda, Step Functions, RDS, S3, and CloudFormation
Integrate application security tools and scanning capabilities into SDLC pipelines, including onboarding scanners, normalizing findings, and translating results into enforceable security controls
Partner with technical leads and architects on AI scanning capabilities and the AppSec AI Harness, advancing agentic vulnerability analysis and remediation from proof of concept to production
Design integration patterns between AI capabilities and the security orchestration platform, including security-finding ingestion, validation of AI-generated remediation, and output-quality measurement
Integrate AI capabilities into platform architecture, engineering standards, and delivery roadmaps
Serve as a technical subject matter expert for AI-enabled application security and DevSecOps
Design and develop APIs, event-driven integrations, automation services, and CI/CD capabilities for scalable security testing
Improve platform and AI reliability and scalability through automation, observability, and self-service capabilities
Collaborate with security and engineering teams to embed SAST, SCA, container security, and API security testing throughout the development lifecycle
Provide technical leadership and mentorship in AI, application security, and platform engineering
Establish technical direction, manage technical risks, and deliver business-critical solutions
Align engineering priorities with strategic initiatives and drive continuous improvement in architecture, standards, security, and operational excellence

Requirements

What you’ll need

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; 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 designing and implementing APIs, distributed systems, automation solutions, and CI/CD pipelines
Experience operating production platform services, including observability, reliability, and operational engineering practices
Demonstrated ability to lead complex technical initiatives, collaborate and influence across organizational boundaries, and mentor engineers
Ability and willingness to learn and apply new technologies as platforms, AI capabilities, and security requirements evolve
Preferred: Experience with Amazon Bedrock, application security, DevSecOps, secure software development, Snyk, Wiz, JFrog Xray, automated code remediation, enterprise AI/data platforms, platform engineering, DevOps, CI/CD engineering, enterprise-scale automation, AWS certifications, or demonstrated applied AI engineering experience
Must be able to work without visa sponsorship; Vanguard is not offering visa sponsorship for this position

Benefits

Comp & perks

Hybrid working model designed to provide flexibility and enable in-person learning, collaboration, and connection
Opportunities to learn and develop skills as individuals and as a team