{"id":518602,"url":"https://alion.io/job/prudential-singapore-ai-application-engineer","title":"AI Application Engineer","company":{"id":232568,"name":"Prudential Singapore","domain":"prudential.com.sg","url":"https://alion.io/company/prudential-2","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workday","truth_index":{"grade":"B","score":81,"open_postings":54,"ghost_share":0,"stale_share":0.574,"repost_share":0,"time_to_fill_p50_days":61,"computed_at":"2026-11-01T06:10:25Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"senior","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Taipei, Taiwan"],"countries":["TW"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":23000,"max_usd":61000,"period":"year","method":"global_role_cell_scaled_by_country","sample_n":2365},"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AgentOps","optional":false},{"name":"AI Agents","optional":false},{"name":"GCP","optional":false},{"name":"Multi-Agent Systems","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"Vertex AI","optional":false},{"name":"A2A","optional":true},{"name":"Agile","optional":true},{"name":"Apache Kafka","optional":true},{"name":"AWS","optional":true},{"name":"Azure","optional":true},{"name":"CI/CD","optional":true},{"name":"Clean Architecture","optional":true},{"name":"Context Engineering","optional":true},{"name":"Copilot","optional":true},{"name":"Docker","optional":true},{"name":"Firestore","optional":true},{"name":"GitHub","optional":true},{"name":"GitHub Actions","optional":true},{"name":"Google ADK","optional":true},{"name":"Google BigQuery","optional":true},{"name":"Google GKE","optional":true},{"name":"Human-in-the-Loop","optional":true},{"name":"Informatica","optional":true},{"name":"Kubernetes","optional":true},{"name":"Langfuse","optional":true},{"name":"LLM Guardrails","optional":true},{"name":"LLMOps","optional":true},{"name":"Model Context Protocol","optional":true},{"name":"Multimodal AI","optional":true},{"name":"n8n","optional":true},{"name":"PostgreSQL","optional":true},{"name":"Power BI","optional":true},{"name":"Prompt Engineering","optional":true},{"name":"Qdrant","optional":true},{"name":"Redis","optional":true},{"name":"SQL","optional":true},{"name":"Terraform","optional":true}],"status":"live","first_seen_at":"2026-03-04T00:00:00Z","employer_posted_date":"2026-03-04","last_verified_at":"2026-11-01T17:41:07Z","board_verified":true,"closed_at":null,"days_open":242,"trust":{"level":"stale","repost_count":0,"flags":["stale"],"days_open":242},"description":"Prudential’s purpose is to be partners for every life and protectors for every future. Our purpose encourages everything we do by creating a culture in which diversity is celebrated and inclusion assured, for our people, customers, and partners. We provide a platform for our people to do their best work and make an impact to the business, and we support our people’s career ambitions. We pledge to make Prudential a place where you can Connect, Grow, and Succeed.\nWe are seeking a skilled and passionate AI Application Engineer to join our global team. The ideal candidate will have a strong background in Python backend development, fluency in Mandarin and English, and experience with multi-agent systems, LLMs, and RAG. Knowledge of GCP Vertex AI and AgentOps is a plusAbout the Role:\nJoin our global insurance leader as an AI Application Engineer! We are seeking a skilled and passionate individual to develop the AI-powered solutions that will transform our business. You'll play a crucial role in building a cutting-edge AI platform based on multi-agent system architecture, pushing the boundaries of what's possible with AI.\nJob Responsibilities:\nCurrent Context:\nDesign, develop, and maintain the backend infrastructure for our AI platform, focusing on multi-agent system architecture.\nDevelop and optimize prompts for large language models (LLMs) and other AI models.\nImplement and manage LLMOps/AgentOps pipelines for model training, deployment, and monitoring.\nImplement and manage relational (RDB) and NoSQL databases as needed for AI system.\nIntegrate AI models and services with other platform components and applications.\nTroubleshoot and resolve AI backend issues, ensuring performance, scalability, and reliability.\nCollaborate with Data Engineers, Data Scientists, and other stakeholders to define and deliver AI-powered solutions.\nPartner with cross-functional teams globally, communicating platform updates effectively.\n Role Briefly: Multi-Agent Systems, Context Engineering (Prompt, Knowledge, Memory), LLMOps/AgentOps, HITL, AI Model Integration, Responsible AI, RDB, NoSQL, Backend Development, Vibe coding (SDD).\nExpectations for Three Months: Become familiar with our existing technology stacks, not only within your specific role but across the broader data platform ecosystem.\nExpectations Within One Year: Contribute to the development of key components of our AI platform, demonstrating expertise in multi-agent systems and prompt engineering. Specific contributions can be discussed.\nJob Qualification:\nBachelor's or Master's degree in Computer Science, Engineering, or a related fields.\nPossess 5 years or above AI/ ML engineering experiences.\nNon-Technical Skills & Mindset:\n Impact-Driven & Results Focused:Value-Oriented: Focused on delivering solutions that generate significant business value (millions USD impact).\nImpact Conscious: Prioritizes work with the greatest technical and business impact. A focus on enabling data consumption through API creation is a plus.\n\nGrowth & Learning Mindset:Cross-Functional Learner: Eager to learn and understand cross-functional knowledge beyond core expertise.\nTechnology Agnostic Learner: Willing to learn new technologies and adapt to evolving landscapes.\nEfficient Learner: Able to leverage AI tools to maximize productivity and accelerate learning.\nBest Practice Pragmatist: Loves to follow best practices but understands trade-offs and works around limitations when necessary. Demonstrated pro-activeness through contributions to open-source projects is highly valued.\n\n Collaborative & Global Communicator:Team Player: Collaborates effectively in global team environments. Adaptable and comfortable working within an Agile environment.\nExcellent Communicator (English & Chinese): Fluent in both English and Chinese (Mandarin) to effectively communicate with global teams and stakeholders.\n\nTechnical Concepts:\nFundamental computer science knowledge\nRoot cause finding methodologies\nSystematic thinking\nClean code/clean architecture principles and an aversion to over-design\nTechnical Skills:\nPython: Proficient in Python, with experience in AI/ML backend development.\nAgent Technologies: Experience in designing and operating production-grade agentic AI systems with secure retrieval and guardrails, including multimodal applications, multi-agent orchestration, context engineering, memory & knowledge (RAG), and MCP.SQL: Solid SQL skills for data management and querying.\nCloud Development: Hands-on experience with GCP, including hybrid environments with on-premises DCs. Experience with AWS or Azure is also acceptable.\nTechnical Stacks:\n Compute & Hosting: GKE & GCE (RedHat), GCP Vertex AI\nAgentic Framework: ADK, n8n, Copilotkit, etc.\nAgentic Protocols: MCP, A2A, AG-UI, A2UI\nDatabases: Redis, Firestore, PostgreSQL, Qdrant\n Data Technologies: GCP Cloud Composer (Airflow), BigQuery , Kafka Ecosystem (Confluent Cloud, Debezium, Qlik), Informatica, Power BI\nMonitoring & Observability: Langfuse, LGTM, GCP Monitoring, OTel\nCI/CD: GitHub Actions\nInfrastructure as Code: Terraform\n Security: VPC SC & Policy Tags, CMEK (KEK/DEK), Vault\nContainers: Docker, Kubernetes\nAI Tools for Development: Gemini CLI, Github Copilot\nWhat You Can Expect:\nGlobal Impact: Work in a cross-country, multi-lingual environment, collaborating with teams across the globe.\nMassive Scale: Contribute to solutions that impact a large volume of customers.\nStrategic Focus: Be at the forefront of a company that strategically focuses on AI and data to drive significant value and impact.\nCross-Functional Collaboration: Work closely with first-line business users, gaining direct insights into their needs and shaping technology solutions that address real-world challenges.\nMeaningful Technology: Make technology truly impactful, driving innovation and solving critical business problems.\nPrudential is an equal opportunity employer. We provide equality of opportunity of benefits for all who apply and who perform work for our organisation irrespective of sex, race, age, ethnic origin, educational, social and cultural background, marital status, pregnancy and maternity, religion or belief, disability or part-time / fixed-term work, or any other status protected by applicable law. We encourage the same standards from our recruitment and third-party suppliers taking into account the context of grade, job and location. 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