Gorilla Logic is looking for a Senior Full-Stack Software Engineer to join a client-facing product team focused on building and improving high-traffic, user-facing web experiences.

In this role, you will work across a mature Ruby on Rails monolith and React frontend, owning features from architecture and implementation through testing and production release. You will contribute to a conversion-sensitive product experience where experimentation, measurable outcomes, and continuous iteration are central to how the team works.

You will also have the opportunity to build product capabilities powered by LLMs and online AI inference, using modern AI development techniques to reduce friction and improve the user experience.

This is a hands-on senior engineering role for someone who combines strong full-stack technical skills with a product mindset and is comfortable collaborating directly with a US-based client and cross-functional team.

What You’ll Do

Design, build, test, and ship full-stack product features using Ruby on Rails and React.
Work effectively within a large, established Rails monolith, safely extending existing functionality and improving the codebase as you go.
Build and refine React components and user-facing experiences with attention to performance, usability, latency, and conversion.
Own features across backend, frontend, and data rather than handing work off between technical boundaries.
Build product capabilities using LLMs and online AI inference, including prompting, context management, tools, and model reasoning.
Develop AI-powered text generation experiences that improve user workflows and reduce friction.
Design features so their impact on product, funnel, and conversion metrics can be measured.
Instrument and support experiments to evaluate product changes and inform future iterations.
Validate solutions using automated and traditional testing practices, as well as AI evals and tracing when applicable.
Apply strong engineering and system design principles to build observable, scalable, maintainable, and production-ready solutions.
Use agentic and AI-assisted software engineering techniques throughout planning, design, implementation, testing, and maintenance.
Collaborate with Product Managers, designers, and engineers to define solutions and identify technical opportunities and constraints.
Prototype and release MVPs early to gather feedback and support iterative product development.
Balance user experience quality, technical investment, and business objectives when making engineering decisions.
Participate in technical scoping and prioritization, helping stakeholders understand what is possible and where technical complexity exists.

What You Bring

Senior-level professional software engineering experience with strong full-stack development capabilities.
Substantial production experience working with Ruby on Rails, specifically within large, established monolithic applications.
Experience navigating mature Rails codebases, including legacy patterns, broad test suites, and careful database migrations.
Strong, current experience building production applications with React.
Experience with React component composition, state management, and frontend architecture.
Demonstrated ability to own features end-to-end across backend, frontend, and data layers.
Strong product mindset with the ability to consider user experience and business outcomes when making technical decisions.
Experience building or improving products against measurable funnel, conversion, engagement, or similar product metrics.
Experience with experimentation and the ability to evaluate results objectively to inform product decisions.
Strong software quality practices, including automated testing, observability, monitoring, and tracing.
Experience working with modern CI/CD and container-based deployment environments.
Effective use of AI coding agents and AI-assisted development tools as part of day-to-day software delivery.
Strong understanding of software architecture and system design principles for scalable production applications.
Strong written and verbal English communication skills.
Ability to collaborate directly with US-based clients and distributed teams operating in US Central Time.

Nice to Have

Experience integrating LLMs such as Anthropic Claude, OpenAI models, or open-weight models into production applications.
Experience building user-facing features that use online AI inference or text generation.
Practical knowledge of prompt design, streaming responses, latency management, fallback strategies, and AI output guardrails.
Experience implementing evals and tracing to measure and monitor AI-generated content quality.
Experience with A/B testing, experimentation platforms, or feature-flag frameworks.
Experience with Docker, Kubernetes, and Argo CD.
Experience deploying or operating applications in AWS environments.
Experience working on high-traffic consumer, marketplace, or SaaS products.
Experience optimizing forms, onboarding experiences, submission workflows, or other conversion-sensitive user journeys.