AI Architect

Job Title: AI Architect

Location: Hartford, CT (1^st preference) and Atlanta, GA (2^nd Preference)

Duration: 6 Months

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:
• Nic to have 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.