Digital & GenAI Architect - Consulting

Role : AI SME (Subject Matter Expert) Key Roles \& Responsibilities: • Serve as the go\-to expert for AI/ML, GenAI, LLMs, RAG architectures, and agentic systems. • Define AI reference architectures, design patterns, and best practices for enterprise use cases. • Review and validate AI solution designs proposed by architects and development teams. • Provide deep guidance on: • LLM selection (OpenAI, Anthropic, Cohere, LLaMA, Mistral, etc.) • Prompt engineering and prompt lifecycle management • RAG strategies (chunking, embeddings, reranking, multi\-vector retrieval) • Vector database selection and optimization • Evaluate PoCs for technical viability, scalability, security, and cost efficiency. • Advise on fine\-tuning vs RAG vs prompt\-tuning strategies. • Ensure AI solutions follow responsible AI, compliance, privacy, and security standards. • Support complex troubleshooting and performance optimization in production AI systems. • Mentor AI Architects, Senior Developers, and Data Scientists. • exp on supervised, unsupervised, reinforcement \& deep learning • Data processing skills(EDA) using Pandas and NumPy for preprocessing and data manipulation. Required Skills \& Experience: • 18–20\+ years in IT with deep hands\-on AI/ML \& GenAI expertise. • Strong experience in: • LLM architectures and advanced RAG pipelines • Agent frameworks (LangChain, AGNOS, Azure agentic framework, kera) • Vector DBs (Pinecone, postgre sql) • Excellent communication skills for executive and client\-facing discussions. • Ability to translate complex AI concepts into business impact. Additional Qualifications: • Demonstrated expertise in AI/ML and GenAI, with proven impact on enterprise systems. • Advanced knowledge of state\-of\-the\-art model frameworks, AI ethics, and governance. • Experience with MLOps, CI/CD for ML workflows, and model monitoring. • Skilled in communication and translating technical AI principles to both technical and business audiences.