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#body.unify div.unify-button-container .unify-apply-now: focus, #body.unify div.unify-button-container .unify-apply-#body.unify div.unify-button-container .unify-apply-now: focus, #body.unify div.unify-button-container .unify-apply-Job Title: Lead AI Engineer
Job Location: Inflight Catering Centre 1
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About Us
SATS is Asia's leading provider of food solutions and gateway services. Using innovative food technologies and resilient supply chains, we create tasty, quality food in sustainable ways for airlines, foodservice chains, retailers and institutions. With heartfelt service and advanced technology, we connect people, businesses and communities seamlessly through our comprehensive gateway services for customers such as airlines, cruise lines, freight forwarders, postal services and eCommerce companies.
Fulfilling our purpose to feed and connect communities, SATS delights customers in over 55 locations and 14 countries across the Asia Pacific, UK, and the Middle East. SATS has been listed on the Singapore Exchange since May 2000. For more information, please visit www.sats.com.sg.
Job Description:
About Us
Headquartered in Singapore, SATS Ltd. is one of the world’s largest providers of air cargo handling services and Asia’s leading airline caterer. SATS Gateway Services provides airfreight and ground handling services including passenger services, ramp and baggage handling, aviation security services, aircraft cleaning and aviation laundry. SATS Food Solutions serves airlines and institutions, and operates central kitchens with large-scale food production and distribution capabilities for a wide range of cuisines.
SATS is present in the Asia-Pacific, the Americas, Europe, the Middle East and Africa, powering an interconnected world of trade, travel and taste. Following the acquisition of Worldwide Flight Services (WFS) in 2023, the combined SATS and WFS network operates over 225 stations in 27 countries. These cover trade routes responsible for more than 50% of global air cargo volume. SATS has been listed on the Singapore Exchange since May 2000. For more information, please visit www.sats.com.sg
Why Join Us
At SATS, people are our greatest asset and we build our success on the knowledge, expertise and performance of every contributor, by embracing diversity and uniqueness. As part of our holistic approach and commitment to embracing FAM (Fulfilling, Appreciated, Meaningful) in the workplace, we offer the runway to develop Fulfilling careers that foster your career growth, recognising and Appreciating the strength of talent and capabilities that we continue to build internally; and inspiring and encouraging each other to make Meaningful contributions in the work we do at SATS.
Key Responsibilities
We are hiring Lead AI engineering role for someone who wants to bring deep software architecture and cloud infrastructure experience into AI/ML and GenAI systems. You will design, build, and operate the platform that our production-grade AI/ML, GenAI, Simulation, sematic layer, knowledge base, RAG, OCR.
Expect to spend the majority of your time building: writing production code, architecting and provisioning cloud infrastructure, and debugging systems in production for GenAI — with technical mentorship and architecture reviews as a smaller part of the role, not the main one.
ML & GenAI Platform Engineering
Design and build scalable ML/GenAI pipelines (batch & real-time)
Build and operate model-serving infrastructure, profile and optimize inference latency in edge compute
Build RAG pipelines, LLM orchestration frameworks, and multi-agent/agentic workflow systems
Build and maintain vector database and embedding pipeline infrastructure
Build and maintain company knowledge base
Build and unify key components of AI Platform, e.g. API gateway, guardrail, auth enabled MCP/tool-calling, tracing
Deep dive into best practice for context management, harness, agent memory management
MLOps & Reliability
Implement model versioning, monitoring, and retraining pipelines
Build integrated data flywheel for eval and model improvement
Setup best practice for data versioning
Ensure reproducibility and reliability of ML systems end-to-end
Software Architecture
Make architecture decisions for the platform, then build the core pieces yourself as reference implementations others build on
Implement shared libraries and reusable building blocks (self-service deployment, GenAI services/APIs) rather than just specifying them
Review code and architecture for the rest of the team
Cloud & Infrastructure
Architect and build the cloud infrastructure (AWS, Azure, or GCP) the platform runs on — compute, networking, IAM, storage, managed Kubernetes
Write and maintain infrastructure-as-code (Terraform or equivalent)
Build and maintain end-to-end CI/CD pipelines for ML/GenAI workloads
Own cost and performance optimization of cloud and LLM infrastructure
Collaboration
Work directly with data scientists and AI Engineers to productionize models
Partner with the Head of AI on technical roadmap and cloud/vendor decisions
Evaluate emerging GenAI tools and frameworks hands-on before recommending adoption
Key Requirements
Degree qualifications at the Bachelor's, Master's, or PhD level in Computer Science, Mathematics, or a closely related field.
With minimum 10 to 12 years in software engineering or GenAI Platform Engineering.
Must-have : deep, hands-on experience with at least one major cloud platform (AWS, Azure, or GCP) — experience in building and operating a production infrastructure
Strong Python experience and hands-on expertise in: Docker, Kubernetes, Terraform/IaC, CI/CD pipelines, MLflow.
Hands-on experience building and running Agentic AI applications/harnesses in production e.g. tool-calling agents, multi-agent orchestration, agent evaluation/observability.
Ongoing commitment to training and professional development in AI/ML, GenAI, and the aviation domain — Cargo Handling, Ground Handling, Ground Freight, and Food Solutions.
Experience in aviation, logistics, or supply chain industries.
Familiarity with production Optimization (Operations Research), Computer Vision, or Simulation systems, OCR.
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