AI Architect

Overview

Remote
Full Time

Skills

Software Design
Use Cases
Pricing
Optimization
Cloud Computing
Amazon Web Services
Google Cloud
Google Cloud Platform
Product Development
Product Requirements
Algorithms
Workflow
Training
Testing
Scalability
Risk Management
Privacy
HIPAA
ISO 9000
Regulatory Compliance
Collaboration
IT Operations
IT Management
Mentorship
Innovation
Natural Language Processing
Generative Artificial Intelligence (AI)
Machine Learning Operations (ML Ops)
Continuous Integration
Continuous Delivery
Microservices
Docker
Kubernetes
Underwriting
Fraud
Soft Skills
Analytical Skill
Conflict Resolution
Problem Solving
Communication
Computer Science
Artificial Intelligence
Cloud Architecture
Microsoft Azure
Machine Learning (ML)
Actuarial Science
Insurance
Analytics

Job Details

Position Overview:

We are seeking an AI Architect to lead the design, development, and deployment of AI-powered capabilities for our next-generation insurance product. This role will be responsible for defining the AI architecture, integrating advanced machine learning models, collaborating with actuarial and underwriting teams, and ensuring scalable, secure, and compliant AI solutions across the product lifecycle.

Key Responsibilities:

AI Architecture & Solution Design

  • Design end-to-end AI/ML architecture for insurance-specific use cases such as underwriting automation, risk scoring, fraud detection, customer personalization, and pricing optimization.
  • Select and define the appropriate AI technologies, model architectures (LLMs, predictive ML, NLP, vision models), and data pipelines.
  • Build scalable ML systems using cloud-native solutions (AWS, Azure, or Google Cloud Platform) and ML Ops frameworks.
  • Insurance Product Development
  • Collaborate with product managers, actuaries, and underwriting SMEs to translate insurance product requirements into AI-enabled functional components.
  • Develop AI models that support rating algorithms, claims triage, eligibility checks, policy servicing workflows, and agent enablement.
  • Ensure AI outputs comply with insurance regulations, underwriting guidelines, and internal governance.
  • Model Engineering & Deployment
  • Lead development, training, validation, and deployment of ML models.
  • Implement MLOps pipelines for automated model testing, monitoring, drift detection, and versioning.
  • Optimize AI performance for accuracy, fairness, explainability, and scalability.
  • Security, Compliance & Risk Management
  • Ensure data privacy and security compliance (e.g., HIPAA, GDPR, ISO standards depending on geography).
  • Implement responsible AI frameworks including explainability, bias mitigation, and model auditability.
  • Collaborate with risk and compliance teams to meet regulatory expectations for insurance AI models.
  • Cross-Functional Collaboration
  • Partner with engineering, actuarial science, underwriting, and IT operations teams.
  • Provide technical leadership and mentoring to data scientists, ML engineers, and developers.
  • Drive innovation through POCs, technology evaluations, and continuous modernization.

Required Qualifications

Technical Skills

  • 4+ years of experience in AI/ML engineering, architecture
  • Expertise in ML frameworks, LLMs, NLP, and generative AI.
  • Strong background in cloud architecture (Azure).
  • Good experience using azure ai services and azure agent frameworks- Mandatory with GHCP
  • Experience implementing MLOps (CI/CD pipelines, model monitoring tools).
  • Hands-on experience with APIs, microservices, and containerization (Docker, Kubernetes).
  • Insurance Industry Experience
  • Deep understanding of insurance processes in at least one line of business:
  • P&C (auto, home, commercial)
  • Experience building or integrating models for underwriting, rating, or fraud detection.

Soft Skills

  • Strong analytical and problem-solving abilities.
  • Excellent communication skills with the ability to explain AI concepts to non-technical stakeholders.
  • Ability to lead cross-functional teams in a fast-paced environment.

Preferred Qualifications

  • Bachelor's or master's in computer science, AI, or related field.
  • Certifications in cloud architecture ( Azure Architect).
  • Experience with interpretable ML techniques relevant to regulated industries.
  • Background in actuarial science or insurance analytics is a strong plus.
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.

About Spark Tek Inc