AI Architect

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 such as OpenAI, Azure OpenAI, and 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

Requirements

• 5+ years of experience in software development or 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 or Architect and guide teams

Preferred Qualifications

• Experience with RAG (Retrieval-Augmented Generation)
• Knowledge of vector databases like Pinecone, FAISS, or Chroma
• Cloud experience with Azure, AWS, or GCP
• Exposure to LangChain, Semantic Kernel, or LlamaIndex
• Understanding of AI security, governance, and cost optimization