About the Company
We are working with A1, a company incubated and backed by BJAK, whose mission is to build the next generation of AI-native applications that fundamentally change how people communicate and get things done. A1's first application, AI Email Triage, reimagines email by moving users from reading and writing emails to learning from and approving AI-completed work-- making it efficient, smart and delightful.
A1's core capabilities are Agentic AI - AI that can reason through multi-step workflows and use external tools to complete tasks; Permission-Based Actions - AI that always asks for approval before taking actions such as sending emails or updating your calendar, keeping users in control; Context & Memory - AI remembers user preferences and past context to deliver increasingly personalised, accurate, and consistent assistance over time.
BJAK is the largest insurance platform in Southeast Asia with presence in Japan, United Kingdom and growing.
Role Summary
In this deeply technical, hands-on role, you will work directly with engineers on system design, evaluation, and trade-offs-defining requirements, shaping how the system works for global users. You will work at the intersection of user needs, model capability, and system constraints, and are responsible for turning AI potential into real, reliable behavior in a real-world application.
Responsibilities
Research and define end-to-end AI system requirements from capability to behavior to user impact
Translate model capabilities, data constraints, and evaluation results into clear product and system decisions
Make hard trade-offs across quality, latency, cost, reliability, and UX
Work closely with ML, backend, and mobile engineers on system design, evaluation, and iteration
Define and evolve evaluation frameworks across offline metrics, online experiments, and human feedback
Drive execution with clear specs, strong judgment, and disciplined prioritization
Ensure systems ship quickly, safely, and reliably, with strong feedback loops
Own product quality end-to-end - correctness, predictability, and user trust
Key Performance Indicators
Product strategy clearly aligns AI capabilities with user needs and company priorities.
AI features deliver real value, are understandable, predictable, and trusted by users.
Decisions balance quality, speed, cost, and reliability effectively under uncertainty.
Roadmaps and priorities are clear, with fast iteration based on real user feedback.
Teams are aligned, focused, and able to execute on AI product goals with minimal friction.
Our Ideal Candidate
Has strong grounding in Computer Science fundamentals, including algorithms, data structures, and system design.
Has solid understanding of ML fundamentals and how modern AI systems behave in production.
Comfortable in reading, reviewing, and discussing technical design documents.
Has hands-on exposure to AI-powered products, including LLM-based systems.
Has experience working with model evaluation, prompt or pipeline iteration, and feedback loops.
Has strong intuition for model limitations, hallucinations, bias, and drift.
Has significant experience owning complex, technical products end-to-end.
Has proven ability to work closely with senior engineers and ML teams.
Has strong judgment and decision-making ability in ambiguous, fast-moving environments.
Able to balance ambition with technical and operational reality.