{"id":4015351,"url":"https://alion.io/job/zus-coffee-regional-ai-engineer","title":"Regional AI Engineer","company":{"id":3012167,"name":"ZUS Coffee","domain":"zuscoffee.com","url":"https://alion.io/company/zuscoffee","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":null,"truth_index":null},"role":"AI/ML","role_family":"AI/ML","seniority":null,"employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Malaysia"],"countries":["MY"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"Claude","optional":false},{"name":"Embeddings","optional":false},{"name":"Function Calling","optional":false},{"name":"Gemini","optional":false},{"name":"JavaScript","optional":false},{"name":"LLM","optional":false},{"name":"Model Context Protocol","optional":false},{"name":"n8n","optional":false},{"name":"OpenAI","optional":false},{"name":"Prompt Engineering","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"Rest API","optional":false},{"name":"SQL","optional":false},{"name":"Structured Outputs","optional":false},{"name":"TypeScript","optional":false},{"name":"AWS","optional":true},{"name":"Azure","optional":true},{"name":"Docker","optional":true},{"name":"GCP","optional":true},{"name":"Git","optional":true},{"name":"GitHub","optional":true}],"status":"live","first_seen_at":"2026-11-10T09:35:27Z","employer_posted_date":null,"last_verified_at":"2026-11-10T09:35:27Z","board_verified":false,"closed_at":null,"days_open":0,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":0},"description":"Position Responsibilities\n\nAI Solution Development\n\nDesign, develop, and maintain AI-powered solutions to support business operations across regional markets.\n\nBuild AI applications using LLMs, AI APIs, AI agents, RAG, and other AI technologies.\n\nIntegrate AI capabilities into existing business systems, platforms, and workflows.\n\nDevelop solutions such as:\n\nAI assistants and chatbots\n\nAI agents for task automation\n\nDocument understanding and information extraction\n\nAI-powered classification and routing\n\nKnowledge-based Q&A / RAG applications\n\nAI summarization and content generation\n\nAI decision-support tools\n\nEvaluate different AI models and services based on accuracy, cost, latency, security, and business requirements.\n\nLLM & AI Integration\n\nIntegrate commercial and open-source AI models through APIs and SDKs.\n\nWork with platforms such as OpenAI, Claude or equivalent AI services.\n\nBuild and maintain prompt templates, structured outputs, tool calling, function calling, and AI workflows.\n\nConnect AI solutions with internal systems through REST APIs, webhooks, databases, and automation platforms.\n\nExplore and implement AI Agent / MCP-based solutions where appropriate.\n\nAI Automation\n\nCombine AI capabilities with automation platforms such as n8n, Lark, and other internal automation tools.\n\nIdentify business processes where AI can reduce manual work, improve response time, or increase operational efficiency.\n\nBuild AI-assisted workflows that can understand information, make structured decisions, and trigger downstream actions.\n\nWork closely with Automation Engineers to integrate AI components into end-to-end automation solutions.\n\nAI Operations & Maintenance\n\nMonitor AI applications and identify issues related to:\n\nModel responses\n\nPrompt failures\n\nAPI errors\n\nLatency\n\nToken usage and cost\n\nData quality\n\nIncorrect or unexpected outputs\n\nPerform basic debugging and root-cause analysis.\n\nContinuously improve AI solutions based on user feedback and production performance.\n\nEstablish appropriate AI evaluation, testing, monitoring, and quality-control mechanisms.\n\nMaintain documentation covering architecture, prompts, models, APIs, data sources, and operational procedures.\n\nAI Governance & Security\n\nEnsure AI solutions follow company requirements for data privacy, access control, security, and responsible AI usage.\n\nUnderstand the risks associated with confidential business data being sent to external AI services.\n\nImplement appropriate controls for sensitive data, permissions, and AI-generated outputs.\n\nEnsure AI applications have appropriate human review or approval mechanisms where required.\n\nRegional Collaboration\n\nWork with regional business, operations, product, technology, and data teams to understand AI opportunities and requirements.\n\nTranslate business requirements into practical AI solutions.\n\nSupport deployment and adoption of AI solutions across different countries and markets.\n\nUnderstand regional differences in languages, processes, systems, and business requirements.\n\nCommunicate technical limitations, risks, and trade-offs clearly to stakeholders.\n\nEscalate architecture, data, security, or AI-quality issues early.\n\nRequirements\n Qualifications & Education\n\nBachelor’s degree in Computer Science, Information Technology, Software Engineering, Data Science, Artificial Intelligence, or a related field.\n\n1–3 years of experience in software development, AI engineering, automation engineering, or a related technical role.\n\nHands-on experience building applications using LLMs or AI APIs.\n\nStrong analytical and problem-solving skills.\n\nAbility to independently research, prototype, test, and deploy new AI technologies.\n\nGood communication and interpersonal skills.\n\nAbility to work independently while managing multiple AI projects.\n\nStrong attention to detail and focus on reliability and quality.\n\nExperience working with business stakeholders and translating business requirements into technical solutions is preferred.\n\nRequired Skillsets - AI & LLM\n\nBasic to intermediate experience with LLMs and Generative AI.\n\nExperience with at least one major AI platform/API such as OpenAI, Claude, Gemini, or equivalent.\n\nUnderstanding of:\n\nPrompt engineering\n\nStructured outputs\n\nFunction/tool calling\n\nContext windows\n\nToken usage\n\nEmbeddings\n\nRAG concepts\n\nAI Agents\n\nRequired Skillsets - Programming\n\nBasic to intermediate programming experience in Python or JavaScript/TypeScript.\n\nAbility to read, modify, debug, and maintain existing code.\n\nUnderstanding of software development fundamentals such as:\n\nFunctions\n\nAPIs\n\nError handling\n\nAuthentication\n\nData structures\n\nLogging\n\nRequired Skillsets - API & Data\n\nGood understanding of REST APIs & JSON.\n\nFamiliar with webhooks and asynchronous API interactions.\n\nBasic to intermediate knowledge of SQL and databases.\n\nUnderstanding of data transformation and validation.\n\nRequired Skillsets - AI Application Development\n\nExperience building AI-powered applications, chatbots, assistants, or automation is preferred.\n\nFamiliarity with RAG / vector databases is a plus.\n\nFamiliarity with MCP (Model Context Protocol) or AI Agent frameworks is a plus.\n\nExperience integrating AI with n8n, Lark, or other automation platforms is a plus.\n\nRequired Skillsets - Engineering & DevOps\n\nFamiliar with Git/GitHub and basic software development workflows.\n\nBasic understanding of deployment, environment variables, authentication, and application configuration.\n\nFamiliarity with cloud services such as AWS, Azure, or GCP is a plus.\n\nExperience with Docker/containerized applications is a plus.\n\nSkills\nAI-Powered Design Tools, Software Development, 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