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G2 is the world's largest software marketplace, recently unified with Capterra, SoftwareAdvice, and GetApp to create a comprehensive B2B software insights platform serving 200M+ annual visitors with 6M verified reviews. The company is transforming how software buyers and sellers make decisions in the age of AI.
As a Senior Software Engineer, you will architect and deliver AI-powered products and features end-to-end, with primary focus on building agent-first solutions. You'll spend approximately 60% of your time on implementation—designing and building AI agents that apply prompts, context, tools, and model reasoning to fulfill user journeys, automate processes, and generate content. You'll own solution quality across the full stack, from architecture through production release, applying sound engineering principles to ensure systems are observable, maintainable, scalable, and production-ready. You'll validate solutions using traditional QA, model-based evaluations, and agent tracing.
About 35% of your time will be spent actively shaping product definition alongside designers and product managers. You'll ideate, explore, and prototype with stakeholders, help prioritize options, and ship features and MVP iterations early that advance high-visibility organizational goals. You'll partner with engineering peers to identify what technology enables and what creates implementation friction, bringing that perspective into scoping and prioritization.
The remaining 5% involves influencing other engineers through knowledge-sharing, championing AI solutions for engineering and product tasks, and accelerating team execution.
You'll need 5–8 years of software engineering experience building enterprise-scale applications. Strong proficiency in TypeScript/JavaScript or Python is required, along with familiarity with modern frameworks (React, Next.js, Rails). You should have broad full-stack ownership and comfort directing AI agents across frontend and backend. Deep understanding of data schemas, databases, APIs, and AWS infrastructure is essential, including hands-on experience with performance testing, logging, and monitoring. Hands-on experience building AI and agent-powered features using frontier models (OpenAI, Anthropic, Google) is required. You should be comfortable working AI-first: delegating to AI agents like Claude Code or Codex, reviewing outcomes, and guiding architecture as part of daily workflow. Understanding of frontier and open-weight model strengths and limitations, plus experience with continuous delivery via feature flagging and trunk-based development, round out the profile. Golang experience is a plus.
