AI Full Stack Engineer

About Ruby Advisory

Ruby Advisory builds human-first AI systems for ambitious teams.

We help companies find where time, energy, and efficiency are leaking inside their daily work, then build practical AI systems that give that value back. Our work lives inside the workflows teams already rely on: lead follow-up, company knowledge, admin and operations, proposal drafting, client delivery, internal tools, and repeatable processes that are too important to stay manual.

Ruby’s approach blends build, implementation, and education. We design systems around how a team actually works, help those systems become part of the business, and teach people how to use AI with confidence in their real work.

About The Role

We are hiring an AI Systems Developer who can build, operate, and improve AI-powered systems for Ruby and our clients.

This role combines software development, systems engineering, AI automation, workflow design, and technical operations. You will work from real client context: calls, transcripts, documents, workflows, data, existing tools, business goals, and messy operational details. From there, you will help decide what should be built, how it should work, and how to ship it.

You should be a strong coder and a daily AI power user. We want someone who is actively using modern AI tools, testing new models, improving their development workflow, and staying close to where the AI tooling ecosystem is moving.

What You Will Work On

• AI-powered client workflows
• Full agent builds for companies
• Custom AI software products and SaaS-style tools
• Internal tools and operating systems
• Automations for repeated business processes
• Agentic workflows and multi-step AI pipelines
• Proposal, research, drafting, and QA workflows
• Lightweight dashboards and review tools
• Integrations across the tools clients already use
• Systems that help teams adopt AI confidently

Responsibilities

• Build AI systems, full agents, automations, internal tools, custom software products, and client delivery workflows.
• Turn client calls, transcripts, notes, documents, and business context into structured plans and working systems.
• Use AI coding tools, LLMs, model APIs, workflow tools, and automation platforms to move quickly.
• Make practical technical decisions when requirements are incomplete.
• Understand how a client team works and design systems that fit their actual process.
• Design agentic workflows that can reason through multi-step tasks, use tools, handle context, and produce reliable outputs.
• Build complex software solutions that combine frontend, backend, AI logic, integrations, data flows, and human review.
• Prototype quickly, test with real use, and improve based on feedback.
• Identify missing context, ask sharp questions, and keep work moving.
• Create reusable components, prompts, workflows, and documentation.
• Help Ruby improve its own delivery systems, internal operations, and client implementation process.
• Stay current with AI tools, models, agent frameworks, coding agents, automation tools, and practical AI use cases.
• Communicate clearly about progress, blockers, tradeoffs, and next steps.

What We Are Looking For

We are looking for someone who is technically strong, highly autonomous, curious, adaptive, and genuinely AI-native.

You should be comfortable taking messy inputs and turning them into useful outputs. A client call becomes a workflow map. A transcript becomes a project plan. A repeated manual task becomes an automation. A scattered knowledge base becomes a system people can actually use.

The right person can move between coding, product thinking, systems design, client context, and deliverable quality. You can go deep on your own, come back with real progress, and explain your decisions clearly.

Required Skills

• Strong coding ability in a modern stack such as TypeScript, JavaScript, Python, or similar.
• Understanding of agentic workflows and agent builds.
• Daily use of AI tools for software development, research, automation, or systems work.
• Experience building with LLMs, AI APIs, agent workflows, automations, or AI-assisted development workflows.
• Ability to build full software solutions, not only prompts or simple automations.
• Ability to turn ambiguous business context into clear technical execution.
• Strong systems thinking across people, tools, data, prompts, workflows, and outputs.
• High autonomy, strong follow-through, and good judgment.
• Cle…