AI Engineer, Virtual Insurance

[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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