AI-Native Developer

CBase Inc
Florham Park, United States of America
yesterday

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English

Job location

Florham Park, United States of America

Tech stack

Clean Code Principles
JavaScript
API
Artificial Intelligence
Amazon Web Services (AWS)
Azure
Cursor (Graphical User Interface Elements)
Software Debugging
DevOps
Programming Tools
Python
Node.js
Systems Development Life Cycle
Next.js
Search Technologies
Software Deployment
TypeScript
Google Cloud Platform
GitHub Copilot
React
Large Language Models
Multi-Agent Systems
Software Application Programming
Generative AI
GIT
Kubernetes
Machine Learning Operations
Api Design
Programming Languages

Job description

An AI-Native Developer (or AI-Native Engineer) experienced to build applications with Artificial Intelligence embedded into their core architecture, workflows, and delivery lifecycle from day one, rather than treating AI as a tacked-on feature. Focus mainly on model training, AI-native developers specialize in using AI to write code, leveraging LLMs (Large Language Models), and constructing agentic workflows to accelerate production.

Core Responsibilities

  • Agentic & LLM System Development: Build autonomous or semi-autonomous agents, orchestrate agent planning loops, manage tool calling, and implement memory modules.
  • AI-Powered Coding: Use AI tools (e.g., Cursor, GitHub Copilot, Claude Code) to rapidly prototype and generate production-ready code.
  • RAG Pipeline Construction: Develop Retrieval-Augmented Generation (RAG) systems using vector databases and semantic search.
  • API/SDK Integration: Integrate LLMs (OpenAI, Anthropic) into applications using function calling, structured outputs, and workflow automation.
  • Production Deployment: Take AI prototypes from Proof of Concept (PoC) to deployment using cloud platforms (AWS, GCP, Azure, Vercel)., * AI-Centric Mindset: Solves problems by blending human judgment with machine intelligence, producing 3-10× more output.
  • Adaptability: Learns new AI tools faster than the industry can create them.
  • Product Focus: Focuses on building, optimizing, and deploying AI applications quickly rather than just researching models.

Requirements

  • Programming Languages: High proficiency in Python and TypeScript/JavaScript (React, Next.js, Node.js).
  • AI Frameworks & Libraries: Experience with LangChain, LangGraph, LlamaIndex, or Semantic Kernel.
  • Vector Databases: Familiarity with technologies such as Pinecone, Chroma, Milvus, or Vertex AI Vector Search.
  • Development Tools: Hands-on experience with AI coding tools such as Cursor, Claude Code, and GitHub Copilot.
  • Software Engineering Fundamentals: Strong understanding of Git, debugging, testing, API design, and clean code principles.

Preferred Qualifications

  • Experience building custom GPTs, Claude Projects, or Multi-agent orchestration.
  • Understanding of AI governance, security, and "human-in-the-loop" mechanisms.
  • Experience with DevOps and MLOps tools (MLFlow, Kubeflow).

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