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.
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.
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.
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.
Python
Node.js
LLM APIs (OpenAI / Anthropic / open-source models)
Prompt engineering frameworks
REST APIs
SQL / NoSQL databases
Experimentation / analytics tools
Optional: vector databases (Pinecone, Weaviate, etc.)
We believe strong products are built by small, high-ownership teams. Engineers at BJAK work closely with product, design, backend, and AI teams to solve meaningful real-world insurance problems. We value technical excellence, speed of execution, and practical decision-making.
Applied AI Engineers are expected to take ownership of AI behavior inside products—not just model usage, but how users experience AI in real workflows.
Build AI-Powered Products - Work on real-world insurance automation systems.
Global Engineering Organization - Collaborate across multiple countries.
International Impact - Products used by millions across Southeast Asia and beyond.
Learning & Development Budget - Support continuous AI and engineering growth.
High Ownership Culture - Own AI features end-to-end.
Modern Engineering Practices - Focus on real-world reliability and scale.
Career Growth - Fast-moving AI product environment.
Competitive Compensation - Attractive salary package.
Fully Remote - Work remotely with globally distributed teams.
Thinks in user workflows, not just model outputs
Strong intuition for how AI behaves in real production environments
Obsessed with making AI useful, not just intelligent
Comfortable working with uncertainty and imperfect models
Strong attention to edge cases and failure behavior
Takes ownership of AI feature quality from design to production
Balances speed with safety and reliability
Researchers who only focus on model training without product integration
Engineers who treat prompts as one-off experiments
People who ignore user experience and real-world behavior
Those uncomfortable with ambiguity in AI outputs
Engineers who cannot evaluate or debug model behavior in production
If there appears to be a fit, we'll reach to schedule 3, but no more than 4 interviews.
Applications are evaluated by our technical team members. Interviews will be conducted via virtual meetings and/or onsite.
We value transparency and efficiency in our hiring process and aim to make decisions promptly. If you've demonstrated the exceptional skills and mindset we're looking for, we'll extend an offer to join us. This isn't just a job offer; it's an invitation to build AI systems that power real-world insurance workflows across global markets.
