1 day ago
Charlotte, NC, USAStaff+
Responsibilities
- Define technical architecture, engineering standards, reusable patterns, and deployment practices for enterprise-scale AI and ML platforms.
- Design resilient AI systems and lead decisions involving model serving, inference optimization, agent architectures, orchestration, observability, and AI infrastructure.
- Partner with AI researchers to operationalize LLMs, trustworthy and responsible AI, and agentic AI systems.
- Lead complex AI engineering, scalability, reliability, performance, governance, security, and cost initiatives from concept through ongoing operations.
- Drive MLOps, LLMOps, AI platform engineering, monitoring, alerting, incident management, capacity planning, and service-level objective practices.
- Own operational excellence and lead response to production incidents, model failures, performance degradation, and system outages.
- Mentor AI and ML engineers, conduct architecture reviews, provide design guidance, and raise technical and operational standards.
- Partner with product, infrastructure, security, and support teams to identify operational risks and improve service reliability.
Requirements
- 10+ years of experience in software engineering, machine learning engineering, AI engineering, or related technical disciplines.
- Deep expertise designing, deploying, and supporting large-scale AI and ML systems in production.
- Demonstrated success leading complex technical initiatives through deployment and ongoing operations.
- Strong knowledge of software architecture, reliability engineering, observability, MLOps, DevOps, and cloud technologies.
- Proven ability to mentor engineers and lead teams through complex technical and operational challenges.
- Preferred experience with foundation models, LLMs, agentic AI architectures, and multi-agent workflows.
- Preferred experience with trustworthy AI, responsible AI, AI governance, model risk management, large-scale inference optimization, AI infrastructure, regulated environments, and mission-critical production systems.
Benefits
- Hybrid working model designed to provide flexibility alongside in-person learning, collaboration, and connection.
- Opportunity to work with AI researchers on advanced technologies and transform research into client value.
- Opportunity to build expertise operating advanced AI systems at scale while collaborating across research, product, and engineering.
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.