Domain Architect- AI/ML, Senior Specialist

Role Overview Vanguard is seeking an AI Architect to design and deliver scalable, secure, and responsible AI platforms and applications that power next-generation client and crew experiences. This role will serve as the technical leader for AI-enabled solutions, partnering closely with engineering, product, data, and enterprise architecture teams to translate business objectives into production-ready AI architectures.

The AI Architect will define solution architectures, drive adoption of AI engineering best practices, and ensure AI systems are scalable, observable, secure, and aligned with enterprise standards. This role balances deep technical expertise with strong collaboration skills, helping engineering teams successfully deliver AI-powered products while advancing Vanguard's AI capabilities.

Derived from the responsibilities of AI/ML architecture, deployment planning, AI solution design, model evaluation, optimization, and stakeholder advisory outlined in Vanguard's AI/ML Domain Architect role. Key Responsibilities 1. AI Solution Architecture Design end-to-end architectures for AI-powered applications and services.

Define patterns for Retrieval-Augmented Generation (RAG), agentic systems, orchestration frameworks, and model integration. Develop scalable architectures leveraging LLMs, vector databases, APIs, and enterprise data platforms. Ensure solutions align to enterprise architectural standards and governance requirements. 2.

AI Platform Engineering Partner with platform teams to design and evolve enterprise AI platforms. Define reusable architecture patterns, reference implementations, and deployment frameworks. Enable secure and scalable deployment of AI services across cloud environments.

Establish observability, monitoring, evaluation, and model lifecycle management practices. This aligns with deployment planning and scalable AI platform responsibilities in the AI/ML Domain Architect role. 3. Responsible AI & Governance Ensure AI solutions comply with responsible AI principles, security standards, privacy requirements, and regulatory expectations.

Define controls for model transparency, explainability, risk management, and auditability. Partner with Enterprise Architecture, Risk, Legal, and Security teams to review and govern AI solutions. Provide architectural guidance for model evaluation and production readiness. 4.

AI Engineering Excellence Establish engineering best practices for prompt engineering, evaluation frameworks, testing, and deployment. Conduct architecture and code reviews for AI-enabled solutions. Drive performance optimization, efficiency, reliability, and cost management of AI systems.

Support experimentation and proof-of-concept initiatives that validate business value. These responsibilities align to solution deployment, model optimization, experimentation, and code review activities described in the AI/ML Domain Architect role. 5.

Data & Model Integration Design architectures that integrate enterprise data sources, event streams, and AI models. Partner with Data Engineering and Data Science teams to operationalize machine learning and generative AI solutions. Define patterns for real-time and batch data processing supporting AI workloads.

Ensure data quality, lineage, governance, and scalability requirements are met. 6. Technical Leadership & Mentorship Provide technical guidance to engineering teams implementing AI solutions. Mentor software engineers and technical leads on AI architecture and emerging technologies.

Act as a trusted advisor for product and technology stakeholders. Stay current with advances in AI technologies, tools, frameworks, and industry best practices. This aligns directly with trusted advisor and AI subject matter expert responsibilities.

Qualifications Required 10+ years of experience in software engineering, distributed systems, and application architecture. 3+ years designing and delivering AI/ML or Generative AI solutions in production. Strong expertise in: Large Language Models (LLMs) Agentic AI architectures Retrieval-Augmented Generation (RAG) LangChain , LangGraph, Semantic Kernel, or similar frameworks Vector databases and semantic search Cloud-native architectures (AWS preferred) APIs, microservices, and event-driven architectures Containerization and Kubernetes (EKS preferred) Experience designing scalable, secure enterprise applications.

Strong understanding of software architecture patterns and engineering best practices. Ability to communicate complex technical concepts to both technical and business stakeholders. Preferred Experience building AI platforms for regulated industries.

Experience with personalization and recommendation systems. Experience with model evaluation, AI observability, and responsible AI frameworks. Familiarity with MLOps and LLMOps practices. Financial services experience preferred. Experience with platform engineering and reusable architectural patterns.

Leadership Expectations Leads through technical expertise and influence rather than organizational authority. Serves as a trusted advisor to engineering and product teams. Demonstrates strong ownership of architectural outcomes. Drives alignment across multiple delivery teams.

Coaches engineers and technical leads to elevate architectural maturity. Balances innovation with pragmatic execution. Education Bachelor's degree in Computer Science , Engineering, Information Systems, or related field (required) Master's degree in Computer Science , Data Science, AI/ML, or related discipline (preferred) What Success Looks Like AI solutions are deployed securely, reliably, and at scale.

Reusable AI architecture patterns accelerate delivery across teams. Responsible AI controls and governance are embedded in solution designs. Engineering teams successfully adopt AI best practices and standards. AI platforms achieve measurable business and client outcomes.

Strong partnership and alignment across Product, Engineering, Data, and Risk organizations. 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.