Overview
On Site
$70 - $80
Contract - Independent
Contract - W2
Contract - 12 Month(s)
Skills
Insurance
Artificial Intelligence
Amazon Web Services
Cloud Architecture
Underwriting
Microservices
Generative Artificial Intelligence (AI)
Machine Learning (ML)
Machine Learning Operations (ML Ops)
Job Details
AI Architect - P&C Insurance (mandatory)
Hartford, CT (1st preference) and Atlanta, GA (2nd Preference) -Onsite
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).
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.