AI Engineering Lead & Platform Architect

Changi Airport Group

Singapore

On-site

SGD 180,000 - 280,000

Full time

4 days ago

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Job summary

Changi Airport Group is seeking a head of AI engineering to lead a mixed in‑house and offshore team in an agile environment, shaping AI strategy, architecture and delivery of AI‑powered products and services across commercial and airport operations.

You will drive responsible AI adoption and establish guardrails, ensuring production readiness while partnering with product, UX and business stakeholders to translate challenges into scalable solutions.

Qualifications

10+ years in software engineering, solution architecture, platform engineering, or related roles.
At least 5 years leading engineering teams delivering complex digital products.
Strong foundation in modern software engineering and distributed systems.
Hands-on proficiency in Python and working knowledge of JavaScript/TypeScript, APIs, event-driven architectures, databases, and customer-facing web applications.
Experience designing and operating secure, scalable solutions on AWS with Bedrock, Lambda, API Gateway, ECS/EKS, S3, RDS, DynamoDB etc.
Experience delivering production-grade generative AI solutions using LLMs, retrieval-augmented generation, embeddings, vector search, tool or function calling, and agentic workflows.
Understanding of prompt, model, retrieval, and agent lifecycle management including testing, guardrails, red-teaming, human oversight.
Experience with infrastructure as code (AWS CDK or Terraform), CI/CD, automated testing, release management, secrets management, and secure software supply chain.
Ability to translate strategy into roadmaps, build-vs-buy decisions, estimates, budgets, and vendor accountability.
Excellent communication, facilitation, and influence for senior leaders.
Learning agility to evaluate evolving AI technologies and apply responsibly in enterprise.
Preferred: aviation/transport/customer loyalty experience.

Responsibilities

Partner with product owners, UX designers, business stakeholders, and engineers to translate challenges into AI-powered products.
Define architecture principles and reusable enterprise capabilities for AI-native products; guide build-versus-buy decisions across platforms and SaaS.
Oversee architecture of AI-enabled solutions integrating LLMs, AI agents, SaaS, AWS services, data sources, and knowledge bases; structure delivery plans and estimates.
Lead multidisciplinary team of full-stack developers and project managers, including offshore resources, to build, operate, and improve AI-powered web apps.
Ensure production-readiness with guardrails, human-in-the-loop workflows, testing, release controls, and operations support.
Establish AI observability, monitoring, and incident management for reliable services.
Oversee AI lifecycle management of models, prompts, retrieval pipelines, agents, and components from experimentation to production.
Provide hands-on technical leadership on complex issues, supporting root-cause analysis.
Recruit, mentor, develop engineers and PMs; foster collaboration across in-house and offshore teams.
Improve engineering productivity through responsible use of AI-assisted development tools.
Foster culture of experimentation, learning, accountability, and knowledge sharing across the developer community.
Provide technology thought leadership; define what good looks like in AI era and differentiate experiences for users.
Plan annual workplan, manage budgets/capacity, oversee offshore partners and vendors.
Define measurable outcomes for AI initiatives and track adoption and value.