AI Engineer

We are seeking a passionate and dedicated AI Engineer to join our team.
💼 Experience: We are looking for candidates with at least 2 years of experience in relevant fields.
📍 Location: Singapore, Singapore
⏰ Work Mode: Work from Office
JD:
Hours:
5-day week, 0830–1730 Mon–Fri (40 hrs/week); on-call/weekend availability required for on-site support and 24/7 call support

Key JD requirements:
Minimum 2 years in a similar role, with broad functional expertise (preferably retail) and technical expertise in AI/ML solution architecture
2+ years leading technical/software engineering teams or managing complex tech projects
2+ years hands-on developing AI/ML solutions and generative AI technologies/frameworks, with at least 2 years specifically in retail, e-commerce, or FMCG
2+ years large-scale backend system development experience
Degree in Computer Science, IT, Programming & System Analysis, Computer Studies, or related discipline; Agile certification a plus
Business Central, Tableau, Microsoft Fabric, or Salesforce certification an advantage
Proficiency in Python or R; cloud data platforms (AWS, Azure, or GCP)
Deep ML/Deep Learning/NLP/Computer Vision knowledge applied to retail (e.g. image search, sentiment analysis)
Generative AI applications in retail (product description generation, virtual try-ons, personalized email copy)
SQL and database schema design — relational and non-relational
Cloud platforms (Azure/GCP), distributed computing, container orchestration (Docker, Kubernetes), MLOps tooling (MLflow, Kubeflow, Airflow)
Familiarity with retail data structures — POS, ERP, CRM systems
Strong commercial acumen tying AI metrics to retail KPIs (e.g. conversion rate); strong storytelling/communication to explain complex AI models to technical and non-technical stakeholders
Available for weekend/off-hours on-site support and 24/7 call support

Scope of work:
Omni-channel customer experience & personalization — AI-driven personalization engines, conversational AI for customer service, in-store layout optimization, customer behaviour tracking; solution architecture, feature development, technical support; customization incl. code structure, extension architecture, theming, caching, API integration (REST/SOAP)
AI systems architecture — design/execute end-to-end platforms for advanced analytics and enterprise AI; align AI solutions with technology architecture and business strategy; strategic input on generative AI, LLMs, and ML frameworks
Leadership & strategy — direct AI project management, solution delivery, vendor/supplier/contractor and internal IT workforce management; evaluate and negotiate with third-party AI vendors and SaaS platforms
Partnership — work with internal/external stakeholders and vendor management; initiate/prioritize projects and process improvements; ensure quality and ROI; translate technical concepts for non-technical audiences
Project & risk management — ensure deliverables on track and meet/exceed expectations; enforce PM principles incl. risk management, prototyping, and PoC delivery for emerging tech
Governance & security — enforce information security policy across IT functions; periodic gap assessments; ensure AI initiatives comply with data privacy regulations
People & resource management — build a performance culture; establish resource allocation/utilization controls
Change management & service excellence — ensure solutions are tested and meet specs/timelines through deployment
Other — monitor solution/project quality, contract & procurement management, IT policy development/review, audit support, ad-hoc tasks