Application Engineering Technical Lead - II

The Application Engineering Technical Lead - II will help shape how AI-powered experiences are built, governed, and scaled across Workplace Technology, with direct influence on the reusable platforms, standards, and engineering practices that enable teams to deliver AI capabilities responsibly.

This role sets technical direction across the team's conversational AI orchestration platform and the surrounding infrastructure, with responsibility for patterns and standards in areas such as:

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

• Conversation history, compliance, and retention pipelines (e.g., WORM-based patterns)

• Model governance and observability (e.g., Arize, evaluation frameworks)

• Knowledge management and retrieval systems (RBAC, ingestion pipelines)

• Model access patterns across multiple providers and model sizes

This role also provides technical evaluation and proof-of-concept leadership as the team explores new AI-powered use cases, helping determine feasibility, implementation patterns, risks, and reuse potential before broader adoption.

Responsibilities:

• Provides expert-level technical leadership for the team's orchestration platform, knowledge management capabilities, and model governance and observability practices. Leads complex development, design, implementation, and architecture specification activities; recommends development options; and approves technical designs and solutions. Ensures deliverables are viable, secure, and testable, with particular focus on compliance-sensitive pipelines. Resolves complex technical issues, supports root cause analysis, and helps prevent recurring technology problems.

• Communicates with key stakeholders on project issues, risks, and implications. Evaluates the impact of change requests on the orchestration platform and influences alignment on technical direction.

• Maintains current working knowledge of AI-amplified PDLC methodology, agent orchestration architecture, model evaluation, observability practices, and emerging model access patterns. Mentors engineers, identifies training needs, and drives adoption of new technical standards across the team.

• This role reviews and approves architecture documentation and diagrams for the orchestration platform and shared AI infrastructure. It also defines technical standards and processes, including patterns for agent onboarding, knowledge ingestion, and conversation compliance.

• Identifies opportunities for continuous quality improvement of technical standards, methodologies, and technologies across the team's platforms.

• Participates in design, code, and test inspections throughout the product life cycle. Serves as a technical consultant at project meetings and presents technical status and issues at milestone reviews.

• Understands and complies with Information Technology and Information Security policies and procedures, and ensures deliverables meet applicable security, compliance, and governance requirements.

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

Qualifications:

Preferred attributes include strong technical judgment, comfort operating in ambiguity, ability to influence without direct authority, and a demonstrated commitment to engineering excellence, responsible AI practices, and continuous learning.

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

• Undergraduate degree or equivalent combination of training and experience. Graduate degree preferred.

• Hands-on experience with agent orchestration or conversational AI platforms (e.g., agent-to-agent/A2A protocols), cloud-native service architecture, and knowledge management/RAG or semantic search systems.

• Experience with LLM observability and evaluation tooling (e.g., Arize or comparable) and exposure to multiple model providers and access pattern design.

• Knowledge of AI-amplified PDLC practices and hands-on experience with languages and tools such as Python, TypeScript, GitHub Copilot, Claude, or comparable AI engineering tools.

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.