Applied AI Engineer

Bjak•Madison, MS

4d•Remote

About The Position

BJAK is Southeast Asia's largest digital insurance platform, building AI-powered products that simplify insurance and financial services for millions of users. We use AI and automation to transform real-world insurance workflows such as quotations, policy issuance, endorsements, claims, and customer operations. We are looking for an Applied AI Engineer to design, build, and optimize AI-powered features that sit directly inside our product workflows. This 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.

Requirements

Strong software engineering background in production environments.
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.

Nice To Haves

Optional: vector databases (Pinecone, Weaviate, etc.)

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.