AI Engineer

RAPSYS TECHNOLOGIES PTE LTD; Singapore; On-site; SGD 90,000 - 130,000; Full time

Job summary

RAPSYS TECHNOLOGIES PTE LTD in Singapore is seeking an AI Engineer to join our team, focusing on AI/ML solution architectures, generative AI, and retail analytics. The role requires 2+ years in related fields and hands-on experience with AI technologies.

You will lead technical projects and collaborate with cross-functional teams, delivering end-to-end AI solutions for retail, e-commerce, or FMCG. On-site 5-day work week with weekend/on-call support as required.

Qualifications

• 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
• Certification in Business Central, Tableau, Microsoft Fabric, or Salesforce 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
• 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

Responsibilities

• 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

Skills

AI architecture

Team leadership

Retail domain knowledge

Python or R

Cloud platforms

Communication

Education

Bachelor degree in CS/IT/related field

Tools

Tableau

Microsoft Fabric

Salesforce

Business Central

Job description

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.

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
• 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