Principal AI Architect – Insurance Solutions

About the role

Infosys is seeking a Principal AI Architect to lead the design and delivery of enterprise‑grade AI, Machine Learning and Generative AI solutions for insurance clients. The role combines deep technical expertise with strategic consulting to translate complex business problems into scalable AI architectures.

Key responsibilities

• Architect end‑to‑end AI/ML solutions across domains such as Generative AI, predictive modeling, computer vision, NLP, and intelligent document processing.
• Lead technical teams through use‑case discovery, data assessment, model development, deployment, monitoring, and continuous improvement.
• Design cloud‑native and hybrid AI platforms on AWS, Azure, and GCP, incorporating LLM frameworks, vector databases, and Retrieval‑Augmented Generation patterns.
• Implement MLOps/LLMOps pipelines, CI/CD for models, and robust monitoring and retraining processes.
• Integrate AI capabilities with enterprise systems via APIs, micro‑services, and event‑driven architectures, and with automation platforms such as UiPath and Power Automate.
• Ensure compliance with AI governance, responsible AI, model risk management, and data privacy/security standards.
• Travel to client sites as needed to support practice development and delivery.

Required profile

• Extensive hands‑on experience designing and delivering AI/ML solutions at scale.
• Proven ability to lead multidisciplinary technical teams on complex engagements.
• Strong problem‑solving skills using design thinking and structured methodologies.
• Experience in the insurance industry or similar regulated domains is a plus.

Required skills

• Python programming
• TensorFlow, PyTorch
• AWS, Azure, Google Cloud Platform
• LangChain, LlamaIndex, Semantic Kernel
• Vector databases and Retrieval‑Augmented Generation (RAG) architectures
• MLOps / LLMOps practices, CI/CD for ML
• Azure OpenAI, AWS Bedrock, SageMaker, Google Vertex AI
• UiPath, Power Automate
• API design, micro‑services, event‑driven integration
• Data pipelines, feature stores, data governance