Ingegnere Full Stack

Rubber Duck is building the semantic trust layer for software engineering .

We are not building “just another coding agent.” We are building the layer that turns fragmented signals from repositories, pull requests, CI, issues, tests, risks, dependencies, and data flows into verifiable engineering context before an AI agent reviews, plans, secures, explains, or modifies code.

We are looking for a Full-Stack Developer who can help us build the product from the ground up.

Someone who is strong across backend, frontend, APIs, databases, product logic, integrations, and developer workflows.

You should know Python and understand AI systems well enough to work around LLMs, agents, embeddings, RAG, evaluations, and AI-powered workflows — but this is not primarily an AI research role .

We are looking for a builder.

A product-minded developer who can ship reliable software, think through architecture, work fast, and understand the difference between an impressive demo and something that can survive real engineering teams.

This could be a on side, hybrid or fully remote position

What you’ll do

You will work on the core Rubber Duck platform, helping us build the systems that connect codebases, developer workflows, AI agents, and engineering context.

You will contribute across the stack: backend services, frontend interfaces, APIs, integrations, data pipelines, internal tools, and product features.

You will work on things like:

• building backend services and APIs;
• developing frontend product experiences;
• integrating with GitHub, CI/CD systems, issue trackers, code repositories, and developer tools;
• working with Python-based services and AI-adjacent workflows;
• implementing product logic around code analysis, context retrieval, engineering signals, and agent workflows;
• designing reliable data flows between repositories, pull requests, tests, issues, and AI systems;
• building internal tooling to help us move faster;
• improving performance, reliability, and developer experience;
• collaborating directly on product decisions, not just executing tickets.

You will work closely with the founding team on a product that sits at the intersection of devtools, AI, software engineering, code intelligence, and enterprise workflows.

Who we’re looking for

We are looking for someone who is primarily a software developer , not just an AI enthusiast.

You should be comfortable building real software systems, making architectural decisions, debugging production issues, and owning features end to end.

You should understand AI enough to work with modern AI tooling, but you do not need to be a machine learning researcher.

You should be interested in questions like:

• How do AI agents understand a real codebase?
• How do we give AI systems better engineering context?
• How do we make AI-generated actions more trustworthy?
• How do we connect code, pull requests, CI, tests, issues, and security signals?
• How do we build devtools that developers actually want to use?

The ideal person is technical, pragmatic, curious, and fast.

You care about clean architecture, but you also know when to ship.

You can move across the stack without needing everything perfectly specified.

You are comfortable with ambiguity, early-stage product decisions, and building systems that may evolve quickly.

Requirements

• Strong full-stack development experience.
• Solid Python skills.
• Experience building backend services, APIs, and product logic.
• Experience with modern frontend development, ideally React, Next.js, or similar frameworks.
• Good understanding of databases, data models, and system design.
• Familiarity with Git, GitHub, pull requests, CI/CD, and modern developer workflows.
• Ability to work with AI-powered systems, LLM APIs, agents, embeddings, RAG, or similar concepts.
• Strong debugging and problem-solving skills.
• Ability to ship features end to end.
• Good written and spoken English.
• Comfortable working remotely and asynchronously.

Nice to have

• Experience building devtools, developer platforms, internal engineering tools, or code intelligence products.
• Experience with GitHub APIs, GitHub Actions, GitLab, Bitbucket, Jira, Linear, or CI/CD integrations.
• Experience with TypeScript.
• Experience with Docker, cloud infrastructure, queues, workers, and background jobs.
• Experience with LLM-based applications, agentic workflows, prompt orchestration, evaluations, or context retrieval.
• Familiarity with code analysis, ASTs, dependency graphs, static analysis, or software architecture tools.
• Experience in B2B SaaS, enterprise software, or early-stage startups.
• Interest in AI coding tools like Cursor, Claude Code, Codex, Copilot, or similar products.

What we are not looking for

We are not looking for someone who only wants to experiment with AI prompts.

We are not looking for someone who can build demos but not production software.

We are not looking for an AI researcher who does not want to work on product engineering.

We are not looking for someone who needs perfectly defined specifications before starting.

We are looking for a real developer who understands AI, not an AI person who sometimes writes code.

Why join Rubber Duck

Rubber Duck is at an important stage: we have a clear vision, strong positioning, and an upcoming launch.

We are building a new category in software engineering: a semantic trust layer between codebases, developers, and AI agents.

You will join early and have a direct impact on the product, architecture, technical direction, and user experience.

This is a chance to build at the frontier of AI and software engineering, but with a very practical mindset: real codebases, real teams, real workflows, real trust problems.

If you want to build serious software for developers in the AI era, this is the right kind of problem.

What we’ll ask you during the interview

• your GitHub profile or relevant portfolio;
• examples of products, tools, or systems you have built;
• a short note on why Rubber Duck interests you.
• A brief explanation of an AI-powered developer tool you think is great, and one thing you would improve about it.