Job description

NAVA Software solutions is looking for a AI Solutions Architect Details: AI Solution Architect - Insurance Domain (Azure & AWS) Location: Remote Duration: 12 months Role Overview As an AI Solution Architect specializing in Azure and AWS, you will lead the design, development, and production deployment of large-scale AI/ML solutions tailored for the insurance industry. You will work closely with cross-functional teams including data scientists, engineers, actuaries, and business leaders to transform business strategy into secure, scalable, and cost-effective AI architectures. Key Responsibilities AI Strategy & Use Case Development • Identify and prioritize AI/ML use cases across the insurance value chain: Underwriting, pricing, claims fraud detection, customer segmentation, policy recommendation engines, and chatbots. • Partner with business stakeholders (e.g., actuaries, underwriters, claims analysts) to define impactful AI-driven solutions that enhance decision-making and operational efficiency. Architecture & Design • Design resilient, scalable, and cloud-agnostic AI/ML architectures using Azure and AWS. • Build and manage data ingestion and transformation pipelines using Azure Data Factory and AWS Glue. • Define and implement MLOps workflows using Azure ML Pipelines, AWS SageMaker Pipelines, and MLflow. Technical Leadership • Lead design reviews, technical workshops, and blueprint sessions. • Mentor engineers and data scientists in best practices for model development, deployment, and cloud-native AI. Solution Development • Implement NLP, computer vision, and deep learning solutions using Azure Cognitive Services, AWS Comprehend, Rekognition, and Bedrock. • Develop microservices/APIs (Python, FastAPI) for real-time inference and batch scoring. • Work with frameworks like TensorFlow, PyTorch, and Scikit-learn. Integration with Insurance Systems • Ensure seamless integration with core insurance platforms: Policy Administration, Claims Management, Billing, CRM (e.g., Guidewire, Duck Creek, Salesforce). • Collaborate with enterprise architects to align AI with broader IT modernization initiatives. Deployment & Operations • Containerize models using Docker, deploy via Kubernetes (AKS/EKS). • Implement CI/CD automation (Azure DevOps, AWS CodePipeline) and observability (CloudWatch, Prometheus, Azure Monitor). Governance & Security • Enforce cloud security and data compliance using IAM, VNet, KMS, and encryption protocols. • Leverage Azure Responsible AI and AWS SageMaker Clarify for explainability, fairness, and auditability. Stakeholder Engagement • Present technical architectures and value propositions to C-level executives, claims directors, and underwriting heads. • Serve as the bridge between business needs and AI/ML capabilities. Required Qualifications Experience: • 8-10 years in AI/ML and software/system architecture. • 5+ years in solution/technical leadership roles. Education: • Bachelor's in Computer Science, Data Science, or Engineering. • Master's or PhD in AI/ML preferred. Cloud Expertise: • Azure: Azure ML, Cognitive Services, Data Factory, Databricks, Cosmos DB • AWS: SageMaker, Comprehend, Rekognition, Glue, Redshift, DynamoDB Tools & Frameworks: • Languages: Python (mandatory), Java or C++ • ML Frameworks: TensorFlow, PyTorch, Scikit-learn • Big Data & Streaming: Spark, Kafka, Hadoop • MLOps/DevOps: Kubernetes (AKS/EKS), Docker, MLflow, Kubeflow, CI/CD pipelines Preferred Qualifications • Certifications: Azure AI Engineer Associate, AWS Certified Machine Learning - Specialty • Advanced AI Expertise: Generative AI (Azure OpenAI, ChatGPT, AWS Bedrock), Prompt Engineering, Agentic AI • Community & Research: Contributions to open-source projects or AI/ML publications • Soft Skills: Strong communication, stakeholder management, and strategic thinking. Team leadership and mentoring

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