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.