About this role
In the United States, bjakcareer seeks a Product Engineer for an AI Email App to build proactive applications that organise daily workflows with minimal prompting. This position suits an experienced technical professional ready to work at the intersection of user needs, model capability, and engineering constraints.
Role Overview
The Product Engineer, AI Email App works at the organization to build AI-native applications focused on long-running workflows, persistent context, and real-world task completion. This hands-on position requires collaborating directly with machine learning and engineering teams to define system behavior, measurement standards, and continuous improvements. The role demands balancing quality, latency, cost, reliability, safety, and user experience.
Key Responsibilities
Requirements
Nice to Have
Skills and Tools
About the Company
bjakcareer builds proactive applications designed to bring intelligence to conversations, errands, organising, and workflows for users globally. Operating as a small, high-talent-density, and hands-on team, the organization maintains a fast-moving, zero-to-one environment where engineers and product leaders exercise broad ownership.
How to Apply
Interested candidates should apply on the official company careers page.
Skills and tech stack
Questions candidates ask
Where is the Product Engineer role located?
The position is located in the United States.
What type of product does this role focus on?
The role focuses on an AI email application designed to bring intelligence to conversations, errands, organizing, and workflows with minimal to no prompting.
What kind of background is beneficial for this position?
An engineering background or experience as a highly technical product manager is considered a strong plus.
What does the interview process involve?
The process consists of three to four interviews conducted via virtual meetings and/or onsite, evaluated by technical team members.
What level of experience is required with AI systems?
Candidates need hands-on experience with AI-powered products, particularly LLM-based systems, along with experience in model evaluation, experimentation, prompting, or AI system iteration.