Applied AI Engineer, Artificial Intelligence (AI) Required, Work From Home
We are looking for an Applied AI Engineer to design, build, and optimize AI-powered features that sit directly inside our product workflows. The Applied AI Engineer role focuses on turning model capabilities into real product behavior, where AI interacts with users, supports decision-making, and powers automation across insurance journeys. This is a fully remote role where you will be part of a global engineering team working across multiple countries to build reliable, scalable AI-powered systems. We have multiple openings for this position. This position is 100% Remote.
Applied AI Engineer Responsibilities:
- Build AI-powered product features integrated into real insurance workflows.
- Design and optimize LLM-based interactions across customer and internal systems.
- Develop prompts, reasoning flows, and structured AI outputs for production use cases.
- Evaluate model performance using real-world data, feedback loops, and experiments.
- Improve reliability of AI outputs through guardrails, fallback logic, and validation layers.
- Work closely with backend engineers to integrate AI capabilities into APIs and workflows.
- Design and implement AI-driven automation features (chat, recommendations, decision support).
- Analyze user behavior and model responses to continuously improve AI performance.
- Collaborate with product, design, and engineering teams to ship end-to-end AI features.
- Contribute to AI system design decisions focused on usability and real-world impact.
Applied AI Engineer Outcomes
- AI features are reliable, consistent, and production-ready across workflows.
- User-facing AI interactions are intuitive and improve task completion rates.
- Model outputs are measurable, testable, and continuously improving.
- AI-driven automation reduces manual work in insurance processes.
- Product teams can safely deploy AI features with controlled behavior.
Applied AI Engineer Qualifications:
- Strong software engineering background in production environments.
- Artificial Intelligence (AI) experience required.
- Experience working with LLMs (OpenAI, Anthropic, or open-source models).
- Familiarity with prompt engineering, structured outputs, and tool use patterns.
- Experience building or integrating AI features into real products.
- Strong understanding of API-based system integration.
- Ability to evaluate AI outputs critically using data and user feedback.
- Experience with experimentation, A/B testing, or evaluation frameworks.
- Strong product sense and focus on user experience.
- Comfortable working in fast-paced, globally distributed teams.
- Tech Stack: A/B Testing, AI, Artificial Intelligence, Anthropic, Evaluation Frameworks, LLM APIs, Node.js, NoSQL, OpenAI, Open-Source Models, Pinecone, Prompt Engineering Frameworks, Python, REST APIs, SQL, Vector Databases, and Weaviate.
Benefits include medical insurance, Dental, Vision, Savings Plan Options, PTO, etc.
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