Domain Architect- AI/ML, Senior Specialist

Vanguard Group, Inc.

$130K — $160K *
Information Technology
8 - 10 years of experience
Job Overview by Ladders

Qualifications

  • 10+ years in software engineering, distributed systems, or application architecture; demonstrated experience with Generative AI in production.
  • Expertise in LLMs, RAG, agentic AI, LangChain/LangGraph, vector databases, APIs, microservices, and cloud-native platforms, particularly Kubernetes/EKS.
  • Experience in designing secure, scalable enterprise applications, preferably in financial services or regulated industries.
  • Strong communication and influencing skills with stakeholders at all levels.
  • Bachelor's degree or equivalent experience required; graduate degree preferred.

Responsibilities

  • Architect end-to-end AI architectures for LLM-powered applications and orchestration frameworks.
  • Define reusable architecture patterns and deployment approaches to expedite delivery.
  • Enable secure and cost-effective AI services in cloud-native environments.
  • Integrate responsible AI practices and regulatory controls into design solutions.
  • Establish best practices for prompt engineering and model lifecycle management.
  • Review architectures and optimize performance in production environments.
  • Mentor engineers and drive alignment across teams on AI architecture and delivery practices.

Benefits

  • Opportunity to work on cutting-edge AI solutions in a collaborative environment.
  • Mentorship and coaching opportunities for growth in AI engineering.
  • Engagement with cross-functional teams to influence major architectural decisions.
  • Flexible work environment aimed at fostering innovation and creativity.
Full Job Description

RoleSummary

Vanguard is seekinga DomainAI Architect to lead thedesignof secure,scalable, and responsible AIsolutionsthat 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 whilebeing hands on andcoaching teams on modern AI engineering practices.

Key Responsibilities

Architecture & Platform Leadership

  • Architectend-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;demonstratedGenerative 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.

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