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.

• 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.