AI-Native Developer / Engineer (Hybrid)

Job Description

Job Description

Mode of Work: Hybrid

Job Description: Seeking an experienced AI-Native Developer / Engineer to build AI-first applications with Artificial Intelligence embedded into core architecture, workflows, and delivery lifecycles from inception. The ideal candidate should possess strong expertise in Large Language Models (LLMs), agentic workflows, Retrieval-Augmented Generation (RAG), AI-powered software development, API integrations, and cloud-native deployments. This role requires hands-on experience building autonomous or semi-autonomous AI agents, orchestrating planning loops, integrating LLMs into applications, implementing memory modules, developing production-ready AI solutions, and accelerating delivery using AI-assisted development tools and modern software engineering practices.

Key Responsibilities:

• Design, develop, test, and deploy AI-native applications with embedded Artificial Intelligence capabilities
• Build autonomous or semi-autonomous agentic systems and orchestrate planning workflows
• Develop and implement Large Language Model (LLM)-based solutions and agentic workflows
• Build Retrieval-Augmented Generation (RAG) systems using semantic search and vector databases
• Integrate OpenAI, Anthropic, and other LLM APIs using function calling, structured outputs, and workflow orchestration
• Utilize AI coding tools such as Cursor, GitHub Copilot, and Claude Code for rapid prototyping and development acceleration
• Develop scalable backend and frontend components using Python, TypeScript/JavaScript, React, Next.js, and Node.js
• Support production deployment of AI applications using AWS, GCP, Azure, Vercel, Docker, and Kubernetes
• Implement testing, debugging, API design, clean code practices, and version control standards
• Support AI governance, security, human-in-the-loop workflows, and responsible AI implementation practices

Additional Responsibilities:

• Collaborate with engineering, product, and business teams to accelerate AI adoption and delivery
• Support Proof of Concept (PoC) to production deployment lifecycle activities
• Optimize AI workflows, agent orchestration, and application performance
• Participate in AI experimentation, innovation, and continuous learning initiatives
• Maintain enterprise software engineering and AI development best practices

Required Skills:

• Strong proficiency in Python and TypeScript/JavaScript (React, Next.js, Node.js)
• Strong experience with Large Language Models (LLMs), agentic workflows, and AI-native application development
• Experience with LangChain, LangGraph, LlamaIndex, or Semantic Kernel frameworks
• Experience building Retrieval-Augmented Generation (RAG) systems and semantic search workflows
• Familiarity with vector databases such as Pinecone, Chroma, Milvus, or Vertex AI Vector Search
• Hands-on experience using AI development tools such as Cursor, Claude Code, and GitHub Copilot
• Strong software engineering fundamentals including Git, testing, debugging, API design, and clean coding practices
• Experience with Docker, Kubernetes, cloud deployment platforms, and MLOps tools preferred
• Understanding of AI governance, security, and human-in-the-loop mechanisms preferred
• Experience building custom GPTs, Claude Projects, or multi-agent orchestration preferred

Qualifications:

• Strong experience building AI-native or LLM-powered applications preferred
• Experience supporting agentic workflows and AI automation initiatives preferred
• Strong adaptability and ability to rapidly adopt emerging AI technologies preferred
• Strong product mindset and ability to quickly deliver scalable AI solutions preferred