Programming.com- AI Architect

 Posted 5 months ago
  
 India
  
5-10 years experience
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AI Summary

The AI Architect will own and design end-to-end AI architecture using the MCP framework and lead AI/LLM integration with enterprise applications. They will also oversee deployment, monitoring, and optimization of AI solutions.

Job Title: AI Architect / Tech Lead – MCP & AI Integration

Location: Pan India

Job Type: Full-Time | Night Shift

Experience: 5+ Years

About the Role

Programming.com is hiring an experienced AI Architect / Tech Lead to design and lead enterprise-grade AI and Gen-AI integrations. The role focuses on MCP (Model–Context–Prompt) architecture, scalable AI solution design, and integration of LLMs into business applications. This is a night-shift role supporting global clients.

Key Responsibilities

  • Own and design end-to-end AI architecture using MCP (Model–Context–Prompt) framework

  • Lead AI/LLM integration with enterprise applications and APIs

  • Define and implement prompt engineering, context management, and model orchestration strategies

  • Evaluate and integrate LLMs (OpenAI, Azure OpenAI, open-source models)

  • Design scalable, secure, and production-ready AI solutions

  • Guide and mentor development teams on AI best practices

  • Collaborate with stakeholders to translate business needs into AI technical designs

  • Oversee deployment, monitoring, and optimization of AI solutions

  • Provide technical ownership and production support during night shift

Required Skills & Qualifications

  • 5+ years of experience in software development / AI solutions

  • Strong hands-on experience with MCP architecture

  • Proven expertise in AI integration and Gen-AI implementations

  • Experience working with LLMs (OpenAI, Azure OpenAI, Hugging Face, etc.)

  • Strong understanding of prompt engineering and context handling

  • Experience with API integrations and microservices architecture

  • Ability to act as Tech Lead / Architect and guide teams

Nice to Have

  • Experience with RAG (Retrieval-Augmented Generation)

  • Knowledge of vector databases (Pinecone, FAISS, Chroma, etc.)

  • Cloud experience (Azure / AWS / GCP)

  • Exposure to LangChain, Semantic Kernel, LlamaIndex

  • Understanding of AI security, governance, and cost optimization

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