What are the responsibilities and job description for the AI-Native Developer / Engineer (Hybrid) position at SIRITECH SOLUTIONS CORP?
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
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
- 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
- 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
- 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