This role builds and supports the AI Powered Experiences team’s conversational AI orchestration platforms and shared AI infrastructure. The engineer will help deliver production-ready GenAI solutions for Workplace Technology by combining hands-on development, AI practitioner experience, and partnership with product and engineering teams. The ideal candidate has experience building and deploying AI-powered solutions, ideally including agent orchestration, conversational AI, or RAG and knowledge management systems on cloud-native infrastructure.

The role will include hands-on work across the following areas:

• Agent orchestration architecture and agent-to-agent (A2A) integration patterns

• Conversation history, compliance, and retention pipelines, including WORM-based patterns

• Model governance and observability, including Arize and evaluation frameworks

• Knowledge management and retrieval systems, including RBAC and ingestion pipelines

• Model access patterns across multiple providers and model sizes

Responsibilities:

In this role, you will be expected to balance hands-on engineering delivery with architecture input, production support, stakeholder partnership, and responsible AI governance practices.

• Provides system analysis, design, development, and implementation for the team’s orchestration platform, including agent registry, health check, and gatekeeper capabilities. Integrates third-party products and model observability tooling as part of scalable AI platform delivery.

• Translates technical specifications into code for complex new or enhancement projects for internal clients, including conversation history and compliance pipelines, segmentation API enhancements, and agent onboarding templates. Develops, tests, and documents code artifacts, and applies software development practices that support automated testing.

• Promotes code through development, test, and production environments for orchestrator services and platform infrastructure. Provides follow-up production support, submits change control requests, and maintains required documentation.

• Applies software development methodology and architecture standards for agent orchestration and cloud-native services. Resolves technical issues within the engineer’s area of expertise, including performance and latency optimization.

• Participates in design, code, and test inspections throughout the life cycle to identify issues. Explains technical considerations at related meetings, including those with internal clients. Performs systems analysis activities across conversation compliance, model governance, and knowledge management workstreams.

• Thoroughly understands client business functions and technology needs. Has a broad understanding of Vanguard's technologies, tools, and applications, including those that interface with business area and systems.

• Interfaces with cross-functional team members, and communicates systems issues at the appropriate technical level for each audience.

• Thoroughly understands and complies with Information Technology and Information Security policies and procedures, and verifies that deliverables meet requirements.

• Contributes to proof-of-concept, prototyping, and exploratory work that informs future AI platform capabilities.

• Participates in special projects and performs other duties as assigned.

Qualifications:

• Demonstrated software engineering experience in enterprise environments.

• Working knowledge of cloud-native infrastructure, specifically AWS, GitHub-based development workflows, deployment pipelines

• Strong programming skills in languages such as Python, JavaScript/TypeScript, or similar.

• Demonstrated ability to work across technical and non-technical stakeholder groups.

• Strong verbal, written, and presentation communication skills.

• Minimum of five years related work experience, with at least two years of development experience.

• Undergraduate degree or equivalent combination of training and experience.

Preferred Qualifications:

• Experience building and delivering software or AI solutions involving agent orchestration, conversational AI, agent-to-agent or A2A protocols, RAG, knowledge management, or semantic search systems.

• Exposure to multiple model providers and evaluation or observability tooling such as Arize or comparable platforms.

• Experience contributing to proof-of-concept, prototyping, or exploratory AI platform work that informs future capabilities.q

Special Factors

Sponsorship

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.