AI Architect/Engineer

- Experience of architecting and solutioning in Gen AI, Agentic AI, classic ML and automation space - Good understanding of Prompt engineering, RAG pipelines, Supervised/unsupervised Model tuning, MLOps/LLMOps pipelines, and AI observability - Experience in Enterprise-grade RAG-based solutions with LLMs (OpenAI, Hugging Face, LLaMA, etc.) and vector databases (Pinecone, Weaviate, FAISS etc.) - Experience in architecting and scaling GenAI chatbots - Experience in Agentic AI solutions with knowledge of Agentic AI frameworks (LangGraph, AutoGen, CrewAI) and orchestration tooling (MCP Servers) in at least 1 Hyperscaler - Ability to design AI interventions for application support, monitoring, and business operations - Good understanding of Responsible AI principles - Ability to design enterprise-level AI/Gen AI platforms/solutions with the client’s existing enterprise stack - Experience in evaluating and selecting appropriate models, frameworks, and orchestration tools - Ability to transform business problems into analytical solutions and foster cross-functional collaboration - Strong articulation, stakeholder management, and consulting skills - Experience working on client proposals – RFI/RFP/Orals stages - Experience in solution presentations to client stakeholders; conducting demos and workshops - Experience leading a team of AI/software engineers - Experience driving productivity and cost optimizations - Skills: Python with AI/ML frameworks (PyTorch, TensorFlow), Prompt Engineering, Langchain, cloud platforms (Azure AI Foundry, AWS Sagemaker/Bedrock, GCP Vertex AI), MLOps/LLMOps tools (MLflow, Kubeflow, Docker, Kubernetes)