AI Solutions Architect - Remote

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