Aift
AI Engineer, Virtual Insurance
Taiwan
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hirly's read of this role
- Seniority
- Mid level
- Country
- TW
- Work mode
- On-site / unstated
- First seen by hirly
- 23 Sept 2026
Derived automatically from the posting. Upload your resume above to see how the role scores against it.
the posting
- [Job Overview]
- We are looking for an experienced AI Engineer to join our engineering team and help drive the development and adoption of AI solutions across the organization. We build digital-first products and continuously explore how AI can improve our products, operations, and the way our teams work.
- You will apply Generative AI and modern AI technologies to real-world business problems, working closely with engineering, product, data, and business teams to turn AI ideas into scalable, production-ready solutions.
- [Responsibilities]
- · Design, develop, and deploy AI-powered applications and services, with a focus on Generative AI and Large Language Models (LLMs).
- · Build AI solutions using techniques such as RAG, prompt engineering, tool/function calling, agents, and structured outputs.
- · Integrate LLMs and AI capabilities into existing products, internal platforms, and business workflows.
- · Develop and maintain backend services, APIs, and data pipelines required to support AI applications in production.
- · Evaluate and experiment with different models, frameworks, and approaches to identify the most effective solution for specific use cases.
- · Build evaluation and monitoring mechanisms to continuously improve AI quality, reliability, latency, and cost.
- · Work closely with Product, Engineering, Data, and business stakeholders to identify high-impact AI opportunities and translate business needs into technical solutions.
- · Prototype new AI ideas quickly, validate their feasibility, and turn successful prototypes into reliable production systems.
- · Stay current with developments in Generative AI and proactively explore technologies that can create meaningful business impact.
- [Requirements]
- · 3+ years of experience in software engineering, machine learning engineering, AI engineering, or a related field.
- · Strong programming skills in Python and solid software engineering fundamentals.
- · Hands-on experience building applications using LLMs or Generative AI.
- · Experience working with commercial or open-source LLMs and related APIs/frameworks.
- · Practical understanding of RAG, embeddings, vector databases, prompt engineering, and LLM application architecture.
- · Experience designing and developing APIs, backend services, or production-grade applications.
- · Familiarity with cloud platforms such as AWS, GCP, or Azure.
- · Good understanding of databases, data processing, and system integration.
- · Ability to independently explore ambiguous problems, experiment quickly, and turn ideas into working solutions.
- · Strong communication and collaboration skills, with the ability to work effectively across technical and non-technical teams.
- [ Nice to Have ]
- · Experience building AI agents or agentic workflows, including multi-step reasoning and tool integration.
- · Experience with LLM evaluation, observability, guardrails, or AI application monitoring.
- · Experience with vector databases or search technologies such as Elasticsearch, OpenSearch, Pinecone, Weaviate, or similar tools.
- · Experience with MLOps / LLMOps, model deployment, CI/CD, Docker, or Kubernetes.
- · Experience optimizing AI applications for latency, scalability, reliability, and cost.
- · Experience with machine learning, NLP, recommendation systems, or other applied AI domains.
- · Experience working in fintech, insurtech, financial services, or other regulated industries.
- · Experience contributing to AI adoption, automation, or developer productivity initiatives within an organization.
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