Bjak
Product Engineer, AI Email App
- Confirmed live in the last 24 hours
- No salary listed
- Mid level
- Full-time
- Remote · United States
- Added 1 month ago
About this role
Product Engineer role building AI-native email applications, bridging user needs, model capabilities, and engineering constraints. You'll define end-to-end AI feature requirements, design evaluation frameworks, and own product quality across reliability, latency, cost, and user trust in a fast-moving startup environment.
What you'll do
- Define end-to-end requirements for AI capabilities from model behavior through user experience
- Translate model capabilities and technical constraints into clear product decisions
- Design and evolve evaluation frameworks across offline metrics, online experiments, and human feedback
- Collaborate with ML, backend, and client engineers on system design and iteration
- Identify AI failure modes and ensure systems behave predictably with graceful recovery
- Drive execution through technical specifications, prioritization, and quality ownership
What they're looking for
- Strong computer science fundamentals and system design
- Production ML systems knowledge and LLM-based product experience
- Model evaluation, experimentation, and prompt engineering
- Technical architecture understanding and deep engineer collaboration
- AI UX patterns and failure mode analysis
- Requirements definition and decision-making under ambiguity
- Hands-on shipping and experimentation mindset
- Constructive technical communication and challenge
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Bjak
Bjak is a Southeast Asian fintech super app offering insurance, payments, savings, wallets, and investment products through a unified platform. The company is hiring full stack engineers, backend engineers, iOS developers, and Android engineers to build scalable features and reliable systems across mobile and web products.
- Industry
- Banking & Finance
- Website
- bjak.com
Likely interview questions
- Tell us about an AI-powered product you've shipped end-to-end—how did you define success and measure quality?
- How would you approach designing an evaluation framework for an AI email feature with competing constraints like latency, accuracy, and cost?