Domain Architect- AI/ML, Senior Specialist
at Vanguard
Posted 8 hours ago
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- United States
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**Senior Domain AI Architect – Lead Design of Secure, Scalable AI Solutions** Vanguard seeks a Senior AI Architect to lead the design of secure, scalable, and responsible AI solutions powering next-gen client experiences. This role involves partnering across multiple departments to translate business needs into production-ready AI architectures. Key responsibilities include defining reusable patterns for LLMs, RAG, agentic systems, model integration, observability, and governance, while being hands-on and coaching teams on modern AI engineering practices. Requirements include a Bachelor's degree in Computer Science, Mathematics, or a related field, and 8+ years of experience in AI/ML domain architecture, along with expertise in relevant technologies and tools such as Python, TensorFlow, PyTorch, and cloud platforms (AWS, GCP, Azure). Proven experience in leading AI architecture projects, driving innovation, and mentoring teams is crucial. Strong domain knowledge, excellent communication skills, and a proven track record of delivering secure, scalable, and responsible AI solutions are essential.
Role Summary
Vanguard is seeking a Domain AI Architect to lead the design of secure, scalable, and responsible AI solutions that power next-generation client and crew experiences. This role partners across Engineering, Product, Data, Risk, Security, and Enterprise Architecture to translate business needs into production-ready AI architectures.
The architect will define reusable patterns for LLMs, RAG, agentic systems, model integration, observability, and governance while being hands on and coaching teams on modern AI engineering practices.
What it means to work at Vanguard:
This is an opportunity to help shape Vanguard’s leading client-facing AI assistant, while advancing the enterprise architecture patterns that enable secure, scalable, and responsible AI across the firm. You will join a high-energy team working on meaningful, visible, and fast-evolving AI capabilities—where we hold a high bar for engineering excellence, collaborate deeply across the enterprise, and make time to enjoy the journey together.
Key Responsibilities
Architecture & Platform Leadership
Architect end-to-end AI architectures for LLM-powered applications, RAG, agentic workflows, orchestration frameworks, APIs, and enterprise data integration.
Define reusable architecture patterns, reference implementations, and deployment approaches that accelerate delivery across teams.
Enable secure, resilient, observable, and cost-effective AI services across cloud-native environments.
Responsible AI & Engineering Excellence
Embed responsible AI, security, privacy, auditability, and regulatory controls into solution designs.
Establish best practices for prompt engineering, evaluation, testing, observability, model lifecycle management, and production readiness.
Review architectures and code, optimize performance and reliability, and support experiments that validate business value.
Influence & Stakeholder Partnership
Serve as a trusted advisor to product, engineering, data, risk, and architecture stakeholders.
Mentor engineers and technical leads on AI architecture, emerging technologies, and delivery practices.
Drive alignment across teams while balancing innovation, governance, and pragmatic execution.
Qualifications
10+ years in software engineering, distributed systems, or application architecture; demonstrated Generative AI solutions in production.
Expertise with LLMs, RAG, agentic AI, LangChain/LangGraph or similar frameworks, vector databases, APIs, microservices, cloud-native platforms, and Kubernetes/EKS.
Experience designing secure, scalable enterprise applications; financial services or regulated-industry experience preferred.
Strong communication, influence, and stakeholder partnership skills.
Bachelor's degree or equivalent experience required; graduate degree preferred.
What Success Looks Like
AI solutions are delivered securely, reliably, and at enterprise scale.
Reusable patterns accelerate adoption across product and engineering teams.
Responsible AI and governance are embedded from design through production.
AI platforms create measurable business, client, and crew outcomes.
10+ years in software engineering, distributed systems, or application architecture.
3+ years designing and delivering AI/ML or Generative AI solutions in production.
Hands-on expertise with LLMs, RAG, agentic AI, LangChain/LangGraph or similar frameworks, vector databases, APIs, microservices, cloud-native platforms, and Kubernetes/EKS.
Strong ability to communicate complex technical concepts to business and technical stakeholders.
Special Factors
Sponsorship
Vanguard is not offering visa sponsorship for this position.About Vanguard
At Vanguard, we don't just have a mission—we're on a mission.
To work for the long-term financial wellbeing of our clients. To lead through product and services that transform our clients' lives. To learn and develop our skills as individuals and as a team. From Malvern to Melbourne, our mission drives us forward and inspires us to be our best.
How We Work
Vanguard has implemented a hybrid working model for the majority of our crew members, designed to capture the benefits of enhanced flexibility while enabling in-person learning, collaboration, and connection. We believe our mission-driven and highly collaborative culture is a critical enabler to support long-term client outcomes and enrich the employee experience.
