AI-Accelerated Full Stack Engineer

AI-Accelerated Full Stack Engineer

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:

* 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

development, testing, and debugging.

* Define, build, and iterate on MVPs without waiting for detailed specs or designs.

* Own the full lifecycle: architecture, development, testing, deployment, and

monitoring.

* Troubleshoot and self-unblock without relying on DevOps or QA.

* Move fast, break down complex problems, and make sound tradeoffs under uncertainty.

What We're Looking For:

* 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.,

pub/sub, message queues, AWS EventBridge, SNS/SQS, Kafka, etc.).

* Comfortable working across frontend (React/Next.js), backend (Node/Python), and

infra (AWS, Docker, Terraform, CI/CD).

* 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.

Nice-to-Haves:

* 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.).

#LI-CG1