GEN AI Architect

Job Summary We are seeking a

GenAI Architect to design, architect, and implement enterprise-scale Generative AI solutions. The ideal candidate will have expertise in

LLMs, RAG, vector databases, agentic AI frameworks, cloud architecture, and CI/CD , with a strong focus on delivering scalable, secure, and production-ready AI applications.

Key Responsibilities

• Design end-to-end GenAI solutions, including RAG, AI agents, copilots, and multimodal applications.
• Translate business requirements into AI architectures and implementation roadmaps.
• Build and optimize retrieval systems using embeddings, chunking, reranking, and vector search.
• Design agentic workflows using LangChain, LangGraph, MCP, and tool-calling frameworks.
• Define scalable cloud architectures and deployment patterns for AI workloads.
• Implement CI/CD pipelines, containerization, monitoring, and MLOps best practices.
• Ensure security, governance, compliance, and Responsible AI standards.
• Provide technical leadership and mentor engineering teams.

Required Skills

• Strong expertise in LLMs, Prompt Engineering, RAG, Fine-tuning, Embeddings, Context Management, and Hallucination Mitigation.
• Experience designing enterprise AI use cases such as copilots, knowledge assistants, intelligent search, summarization, and workflow automation.
• Hands-on experience with vector databases: Pinecone, FAISS, Weaviate, Chroma, Milvus, Azure AI Search, or Elasticsearch Vector Search.
• Experience with LangChain, LangGraph, MCP, Multi-Agent Systems, Memory, Planning, and Guardrails.
• Strong knowledge of cloud platforms (Azure, AWS, or GCP) and AI/ML services.
• Expertise in Docker, Kubernetes, API deployments, CI/CD, DevOps/MLOps, Observability, and Cost Optimization.