3 days ago
Charlotte, NC, USA or Dallas, TX, USASenior
Responsibilities
- Design, develop, and implement secure cloud-native platform services on AWS using services including IAM, ECS, Lambda, Step Functions, RDS, S3, and CloudFormation.
- Integrate SAST, SCA, container, and API security scanners into SDLC pipelines, normalize findings, and translate results into enforceable security controls.
- Develop the AppSec AI Harness and production agentic AI capabilities for vulnerability analysis and developer remediation.
- Design integrations for security findings, AI-generated remediation validation, output-quality measurement, prompt evolution, and model evaluation.
- Build APIs, event-driven integrations, automation services, and CI/CD capabilities for scalable security testing.
- Improve platform and AI reliability, scalability, observability, automation, and self-service capabilities.
- Provide technical leadership and mentorship while setting technical direction, managing risks, and collaborating across security, AI, data, platform, and engineering teams.
- Drive secure development practices, platform architecture improvements, engineering standards, and operational excellence.
Requirements
- 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; a graduate degree is preferred.
- Strong expertise in AWS and cloud-native application and platform architectures.
- Strong software engineering and programming fundamentals across multiple languages, including Node.js and TypeScript; Python is particularly valuable for AI and large language model development.
- Hands-on experience building multi-step, tool-using agentic AI solutions integrated into production systems.
- Experience integrating large language models into production applications, including prompt design, tool or function calling, context management, cost optimization, and latency management.
- Experience evaluating AI-generated output quality and reliability, establishing release criteria, and identifying post-deployment degradation.
- Experience designing APIs, distributed systems, automation solutions, CI/CD pipelines, and production platform services.
- Experience with observability, reliability, and operational engineering practices.
- Demonstrated ability to lead complex technical initiatives, influence across organizational boundaries, and mentor engineers.
- Preferred experience with Amazon Bedrock, application security, DevSecOps, secure software development, Snyk, Wiz, JFrog Xray, automated code remediation, enterprise AI and data platforms, platform engineering, DevOps, CI/CD engineering, and enterprise-scale automation.
- AWS certifications and demonstrated applied AI engineering through production systems, open-source contributions, or published work are preferred.
Benefits
- Hybrid working model designed to combine flexibility with in-person learning, collaboration, and connection.
Tech Stack
Categories
About Vanguard
Vanguard is an investment management company offering low-cost index and active mutual funds, ETFs, brokerage, retirement plans, and financial advice for individual, institutional, and advisor clients. Founded in 1975 by John C. Bogle and headquartered in Valley Forge, PA, it operates a client-owned structure in which its funds own the firm. Its business model centers on asset-based management and advisory fees.