About The RoleAs a Senior Software 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 architecting the solution, delegating implementation to your agents across the full stack, and reviewing and validating what they produce with confidence in their performance. As a technologist, you will be a key voice in defining and refining product concepts and you'll act as a hands-on, in-person technical partner to stakeholders and leadership. 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.
Detailed Responsibilities:Build AI and agent-first products and features [60%]:- 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
Actively participate in product definition as a technologist [35%]:- 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
Be a source of influence for other engineers on the team [5%]:- 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
Minimum Qualifications:We realize applying for jobs can feel daunting at times. Even if you don't check all the boxes in the job description, we encourage you to apply anyway.
- 5-8 years of experience working as a Software Engineer, with proven experience building enterprise-scale applications.
- Solid working proficiency in Typescript/Javascript or Python, and familiarity with modern web application frameworks like React, Next.js, or Rails.
- Broad full-stack ownership; comfortable directing agents across both frontend and backend development.
- Strong understanding of data schemas, databases, APIs, and AWS infrastructure, including how to structure data so it holds up at high volume and returns quickly under load; hands-on experience with performance testing, logging, and monitoring. Golang preferred but not required.
- Hands-on experience building AI and agent-powered features and systems using frontier models from OpenAI, Anthropic, or Google.
- Comfort working AI-first: delegating implementation to AI agents (e.g., Claude Code, Codex, Opencode, Pi), reviewing outcomes, and guiding architecture as part of the daily development workflow.
- Understanding of the strengths and limitations of frontier models and open weight models
- Experience with continuous delivery through feature flagging and trunk-based development
What Can Help Your Application Stand Out:- Experience deploying or fine-tuning open-weight models for specific use cases
- Hands-on experience with agent orchestration frameworks
- Experience with distributed messaging or event-streaming systems (e.g., Kafka).
