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Lead AI Engineer

Airwallex· Engineering
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SG - SingaporeFull-timePosted 2mo ago

About the role

Lead the technical design, execution, and people leadership for Kai, Airwallex’s AI assistant for complex financial work. Build reliable, observable, and safe production AI systems, set technical direction for agent orchestration, retrieval, tool integrations, and observability, and manage AI, backend, and frontend engineers.

Responsibilities

  • You’ll lead the technical design, execution, and people leadership for Kai, Airwallex’s AI assistant for complex financial work.
  • You’ll turn rapidly evolving LLM and agent capabilities into reliable, observable, and safe production systems that understand intent, retrieve business context, reason over products and data, and take appropriate actions.
  • You’ll set the technical direction for agent orchestration, context and retrieval, tool integrations, identity and access control, observability, evaluation, and responsible action-taking, while balancing quality, latency, reliability, cost, security, and time to market.
  • You’ll work closely with Product, Design, Data, Security, Infrastructure, and domain teams to deliver trusted AI products and reusable platforms that can scale across Airwallex.
  • You’ll manage, coach, and develop AI, backend, and frontend engineers, set clear expectations, and raise the engineering bar through hiring, feedback, and technical mentorship.
  • You’ll work from our Singapore office five days a week.

Qualifications

  • 8+ years of software engineering experience, including 2+ years leading, managing, or formally mentoring engineers.
  • Track record of building strong teams and delivering complex products end to end.
  • Deep experience designing and operating scalable agentic architecture, backend systems, or distributed systems.
  • Understanding of retrieval, model integration, agent workflows, evaluation, observability, and changing model behaviour.
  • Disciplined approach to evaluation, monitoring, incident management, performance, testing, and operational readiness.
  • Secure software design understanding (authentication, authorisation, data protection, auditability, abuse prevention).
  • Ability to define and evolve technical architecture across agent orchestration, context and retrieval, tool integrations, identity and access control, observability, and evaluation systems.
  • Experience delivering production-grade AI features from discovery through launch and iteration.
  • Ability to establish product and model success metrics, instrument customer journeys, and use real-world feedback to improve AI usefulness and trustworthiness.
  • Ability to build repeatable, versioned evaluation practices for task success, groundedness, tool use, safety, and domain-specific failure modes.
  • Ability to define launch criteria, staged-rollout and rollback mechanisms, and monitoring that detects regressions as models, prompts, and data evolve.
  • Capacity to drive engineering excellence across service design, APIs, data pipelines, reliability, performance, cost efficiency, testing, incident response, and operational readiness.
  • Ability to define and improve SLOs for critical AI services.
  • Champion robust authentication, authorisation, permission checks, auditability, and human-in-the-loop patterns for agent actions.
  • Create reusable agent platforms, developer tooling, quality frameworks, and engineering standards for safe high-quality AI experiences.
  • Clear communication of technical decisions and risks to stakeholders with cross-functional collaboration.

Skills

Required:Software engineeringLeadership and mentorshipDistributed systems / backend architectureRetrieval and model integration
Last updated Oct 15, 2026. Interested? Apply on the company site.
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