Lead AI Engineer
About the team Kai is Airwallex’s AI assistant, designed to help customers to accomplish complex financial work with great speed and control. We are building trusted agentic experiences that can understand intent, retrieve the right business context, reason over product and data, and take appropriate actions. As Engineering Lead, you will own the technical design, execution, and people leadership for Kai engineering team. You will turn rapidly evolving LLM and agent capabilities into reliable, observable, and safe production systems that solve meaningful customer and business problems. This is a hands-on leadership role. You will set a high bar for architecture and engineering quality, grow a strong team, and work closely with Product, Design, Data, Security, Infrastructure, and domain teams across Airwallex. You will balance rapid learning with the rigor required for a global fintech platform. What you'll do As the Lead engineer in our Generative AI department, you will lead the team and help define the technical and strategic vision for next-generation AI solutions. You will drive engineering excellence across Kai. Your work will set the standard for AI engineering excellence, paving the way for the next wave of intelligent products and services. This role is based in Singapore. Responsibilities: Lead and grow an exceptional team: Manage, coach, and develop a team of AI, backend, and frontend engineers. Set clear expectations, build an inclusive high-performance culture, and raise the engineering bar through hiring, feedback, and technical mentorship.
Evolve technical architecture for Kai: Define and evolve the architecture for agent orchestration, context and retrieval, tool integrations, identity and access control, observability, and evaluation systems. Make sound trade-offs across quality, latency, reliability, cost, security, and time to market.
Build trusted AI products: Lead the delivery of production-grade AI features from discovery through launch and iteration. Establish clear product and model success metrics, instrument customer journeys, and use real-world feedback to continuously improve Kai’s usefulness and trustworthiness.
Make evaluation and safety release disciplines: Build repeatable, versioned evaluation practices for task success, groundedness, tool use, safety, and domain-specific failure modes. Define launch criteria, staged-rollout and rollback mechanisms, and monitoring that detects regressions as models, prompts, and data evolve.
Deliver resilient, scalable systems: Drive engineering excellence across service design, APIs, data pipelines, reliability, performance, cost efficiency, testing, incident response, and operational readiness. Define and improve SLOs for critical Kai services.
Partner across the business: Work closely with Product, Design, Data, Security teams to translate business needs and model capabilities into secure, coherent customer experiences. Communicate technical decisions and risks clearly to stakeholders.
Enable responsible action-taking: Champion robust authentication, authorisation, permission checks, auditability, and human-in-the-loop patterns for agent actions. Ensure Kai behaves predictably and appropriately in the context of Airwallex’s customers, products, and regulatory obligations.
Build for leverage: Create reusable agent platforms, developer tooling, quality frameworks, and engineering standards that allow multiple teams to safely ship high-quality AI experiences.
Who you are We're looking for people who meet the minimum qualifications for this role. The preferred qualifications are great to have, but are not mandatory. Minimum qualifications: Experienced engineering leader: You have 8+ years of software engineering experience, including 2+ years leading, managing, or formally mentoring engineers. You have a track record of building strong teams and delivering complex products end to end.
Hands-on Agent builder: You have deep experience designing and operating scalable agentic architecture, backend or distributed systems.
AI product and platform fluency: You understand the engineering realities of retrieval, model integration, agent workflows, evaluation, observability, and changing model behaviour.
Quality and reliability driven: You bring a disciplined approach to evaluation, monitoring, incident management, performance, and operational readiness. You know that AI quality requires measurement and iteration, not intuition alone.
Security-minded: You understand secure software design and appreciate the importance of authentication, authorisation, data protection, auditability, and abuse prevention in systems that access sensitive data or initiate actions.
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