AI Engineering

Key ResponsibilitiesEnd-to-End Solution Design•    Own the technical solution design for all AI use cases across JSC's procurement, quality assurance, supplier management, and export operations — from intake through to production— producing architecture artefacts, design decisions and technical specifications.•    Work alongside JSC's Enterprise and Cloud Architects on end-to-end solution design — ensuring AI solutions are enterprise-compliant, secure and platform-aligned from day one across Singapore, Vietnam, and India.•    Produce and review architecture artefacts, technical designs, integration patterns, engineering standards, and implementation plans.AI Platform & Services —Design & Oversight•    Own the AI engineering layer onAWS — defining which native services are used for each JSC use case (e.g.,RFQ/quote processing, supplier document intelligence, quality certificate verification, order book reconciliation) and how they connect to JSC's enterprise stack.•    Lead technical design across the core AWS AI stack: Bedrock (LLM orchestration, agents, knowledge bases,guardrails), Agent Core, Sage Maker (ML model deployment, pipelines, MLOps),Textract/Comprehend (document intelligence for invoices, purchase orders, qualitycertificates, and supplier quotes), OpenSearch (vector search, RAG retrieval over supplier and product documentation), Step Functions (pipeline orchestration).Production Engineering &Standards•    Ensure all AI solutions are built to production standards — with appropriate testing, security controls,PII handling, monitoring, logging, resilience, error handling and operational runbooks.•    Own the AI Platform Engineering reuse library — ensuring components, patterns, prompt templates and AWS service wrappers built for one use case (e.g., a supplier document extractor) are packaged and available for reuse across JSC's product lines and regions.•    Lead technical production readiness reviews before any AI solution goes live — covering model risk, security, performance, cost and rollback plan.Team Leadership•    Lead the AI Platform Engineering team across AI engineering, AI solution development, and AI testing disciplines.•    Provide technical direction, coaching, and development support to AI Engineers, AI Engineer Associates, and AI Test Engineers.What We're Looking ForEssential•    7+ years of software or AI engineering experience, with at least 3 years in a senior technical lead or architect role.•    Strong hands-on experience designing and delivering AI / ML / GenAI solutions in production environments.•    Deep understanding of AWS AI and cloud-native services, preferably including Bedrock, Sage Maker, Textract,Comprehend, OpenSearch, Lambda, API Gateway, Step Functions, and S3.•    Strong practical knowledge of Generative AI engineering, including LLM integration, prompt engineering, RAG architecture, embeddings, vector stores, evaluation frameworks, and hallucination controls.•    Exposure to manufacturing, procurement, supply chain, or export/trading operations is a plus (fastener or industrial components industry preferred).