Junior AI-Augmented Product Engineer

Role overview

An early-career engineer is needed to help build a new generation of internal AI-powered tools that support global go-to-market teams. The role sits between product and engineering, partnering with a Platform Owner to gather requirements, write rigorous specifications, orchestrate AI-assisted implementations, and verify quality against strict architectural standards.

Responsibilities

- Partner daily with the Platform Owner to translate business challenges into well-defined product and technical requirements, capturing edge cases, success metrics, and constraints. - Author and maintain high-quality documentation including functional specs, technical specs, data flows, acceptance criteria, and architecture notes aligned to internal standards. - Translate requirements into precise plans and instructions for AI-assisted implementation, coordinating iterative build-and-verify cycles. - Enforce enterprise-grade design patterns, architecture principles, and quality gates during planning, implementation review, and validation. - Run and troubleshoot automated quality checks such as type checking, linting, and tests, diagnosing issues and proposing targeted fixes. - Keep system knowledge current by updating reference documentation, tracking changes across versions, and surfacing ambiguities for resolution.

Requirements

- Demonstrated interest in AI-augmented software development and comfort using advanced AI tools as a daily working partner. - Strong written communication, structured reasoning, and documentation skills, with the ability to frame ambiguous problems clearly. - Working familiarity with modern software development practices, including testing, code review, and version control. - Comfort collaborating across US and EMEA time zones using asynchronous documentation and remote-friendly workflows. - A bias for precision over speed of coding, with the ability to balance stakeholder demands from leaders and individual contributors.

Nice to have

- Prior internship, project, or open-source experience building internal tools or platforms. - Exposure to enterprise architecture patterns, design systems, or large-scale engineering environments. - Interest in growing into a product-engineering hybrid career path rather than a traditional implementation role.