AI Product Engineer, G2

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• 6+ years of professional programming experience in web application and backend environments
• Expert-level proficiency in Typescript/Javascript or Python; strong working knowledge of modern web application frameworks like React, Next.js, or Rails
• Hands-on experience building AI and agent-powered features and systems using frontier models from OpenAI, Anthropic, or Google
• Understanding of the strengths and limitations of frontier models and open weight models
• Regular use of agent harnesses like Claude Code, Codex, Opencode, or Pi as part of the daily software development workflow
• Experience with continuous delivery through feature flagging and trunk-based development

Desirable

• As an AI Product Engineer, you will create new products and features end-to-end which directly contribute to G2’s key organizational goals. Your responsibilities will center around building and delivering AI and agent-first products and features to production with confidence in their performance
• As a technologist, you will be a key voice in defining and refining product concepts to take advantage of opportunities afforded by new tech & greater industry developments. You will adopt industry-leading agentic engineering techniques and leverage “agent-first” ways of working to deliver products, reflecting the realities of today’s software development lifecycle
• Contribute across the full software stack to deliver user journeys to production, owning implementation quality from architecture to release
• Design and build agents that apply prompts, context, tools, and model reasoning to fulfill user journeys, generate content, and automate processes
• Apply sound software engineering and system design principles to produce solutions that are observable, maintainable, scalable, and production ready
• Validate solutions against functional requirements using both traditional QA methods, model-based evals, and agent tracing to ensure quality is measurable and reproducible
• Incorporate agentic software engineering techniques into the development workflow across the SDLC, from planning, design, implementation, testing, and maintenance
• Drive product definition with designers and PMs: ideate, explore, and prototype with stakeholders, then cut down possible options to arrive at deliverable, but well-rounded solutions
• Wholly conceive and ship features & MVP iterations early in the product definition phase that directly advance high-visibility organizational goals
• Strike the right balance between investment in UX quality and tending to practical business needs through the product development process
• Partner with other engineering stakeholders to identify what technology makes possible, and what makes implementing a given product or feature hard. Bring that perspective into project scoping and prioritization
• Share knowledge, techniques, and agentic software engineering practices in async formats and dedicated venues, like technical discussions and team meetings
• Champion the use of AI solutions for engineering and product tasks, accelerate product velocity and team’s execution