BJAK

AI Engineer

• 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

Android Engineer

• Build and maintain production-grade Android applications using Kotlin.
• Design and implement intuitive, responsive mobile interfaces for insurance, payments, and customer workflows.
• Integrate backend APIs for quotations, policy management, claims, and transactional services.
• Contribute to mobile features that incorporate AI-assisted capabilities (e.g., chat experiences, recommendations, automation flows).
• Optimize application performance, responsiveness, battery usage, and memory efficiency across devices.
• Implement analytics, crash reporting, and user behavior tracking to improve product quality.
• Collaborate closely with backend, product, design, and AI/ML teams throughout the development lifecycle.
• Ensure stability, scalability, and security across production mobile systems.
• Continuously improve engineering standards, architecture, and mobile best practices.

Android Software Engineer

Systems Engineer

• Build and operate backend systems that serve AI-powered insurance workflows in production.
• Design and implement AI orchestration layers that connect models, APIs, workflows, and business logic.
• Build inference pipelines for LLM-based and AI-assisted automation systems.
• Optimize latency, throughput, and cost across AI services (caching, batching, streaming, routing).
• Design stable service boundaries between backend systems, ML components, and product APIs.
• Implement observability: logging, metrics, tracing, alerting, and incident response workflows.
• Debug production issues across distributed AI systems and resolve root causes.
• Collaborate closely with frontend, product, operations, and ML teams to ship end-to-end features.
• Continuously improve system reliability, scalability, and performance.

AI Backend Engineer – AI Workflow Systems

Full-stack Engineer

• Build and maintain production-grade iOS applications using Swift and SwiftUI.
• Design and implement intuitive, responsive mobile interfaces for insurance, payments, and customer workflows.
• Integrate backend APIs for quotations, policy management, claims, and transactional services.
• Contribute to mobile features that incorporate AI-assisted capabilities (e.g., chat experiences, recommendations, automation flows).
• Design UX patterns for real-time interactions, including loading states, streaming responses, retries, and fallbacks.
• Optimize application performance, responsiveness, memory usage, and battery efficiency.
• Implement analytics, crash reporting, and user behavior tracking to improve product quality.
• Collaborate closely with backend, product, design, and AI/ML teams throughout the development lifecycle.
• Ensure stability, scalability, and high App Store quality across production releases.
• Continuously improve engineering standards, architecture, and iOS best practices.

iOS Software Engineer

• Build and ship AI features end-to-end (model → system → user experience)
• Design and iterate on prompts, tools, memory, and agent workflows
• Turn raw model outputs into structured, reliable, and predictable behaviors
• Debug issues across the full stack (model, orchestration, infra, UX)
• Optimize for latency, cost, and production reliability
• Develop lightweight evaluation frameworks to measure real-world performance
• Work closely with product and engineering to translate ambiguous problems into working systems