What are the responsibilities and job description for the AI-Accelerated Full Stack Engineer position at Mathys Potestio / The Creative Party®?
About The Role
Our client is hiring an AI-accelerated Full Stack Engineer who builds like it’s their own product. You’ll own features end-to-end—from frontend to backend to infra—and use AI tools to 10x speed, not cut corners.
This role is ideal for engineers who think like founders, move without waiting, and thrive in fast, event-driven systems. You’ll work with a lean, high-agency team that values outcomes over ceremony.
What You’ll Do
Our client is hiring an AI-accelerated Full Stack Engineer who builds like it’s their own product. You’ll own features end-to-end—from frontend to backend to infra—and use AI tools to 10x speed, not cut corners.
This role is ideal for engineers who think like founders, move without waiting, and thrive in fast, event-driven systems. You’ll work with a lean, high-agency team that values outcomes over ceremony.
What You’ll Do
- Build and ship complete features using Next.js, Node.js, TypeScript, Python, etc.
- Design and implement event-driven architectures that support scalable, decoupled systems.
- Use AI tools like GitHub Copilot, GPT-4o, Claude, and LangChain to accelerate
- Define, build, and iterate on MVPs without waiting for detailed specs or designs.
- Own the full lifecycle: architecture, development, testing, deployment, and
- Troubleshoot and self-unblock without relying on DevOps or QA.
- Move fast, break down complex problems, and make sound tradeoffs under uncertainty.
- 7 years of full-stack engineering experience.
- Proven ability to deliver high-quality software from idea to production independently.
- Strong fundamentals in API design, system architecture, and cloud infrastructure.
- Hands-on experience designing and maintaining event-driven architectures (e.g.,
- Comfortable working across frontend (React/Next.js), backend (Node/Python), and
- Startup mindset: you don’t wait for Product, Design, or QA—you step in and drive.
- Bias for action, clarity, and continuous learning.
- Deep familiarity or strong interest in AI tools and workflows that improve engineering velocity and quality.
- Experience with LangChain, vector databases, or RAG pipelines.
- Experience building internal tooling or AI-enhanced developer workflows.
- Exposure to HIPAA/PHI handling and healthcare compliance.
- Experience applying machine learning concepts in production systems (e.g., model inference, feature pipelines, personalization, etc.).
