Define and evolve the architectural blueprint for data and AI systems that support underwriting, claims intelligence, and regulatory reporting.
Architect end-to-end pipelines and platforms that deliver real-time insights into provider risk, litigation trends, and claim severity.
Establish architectural standards and governance aligned with HIPAA, NAIC, and SOC 2.
Design infrastructure to support predictive modeling, risk scoring, and generative AI use cases such as patient safety, claims triage, documentation summarization, and litigation forecasting.
Enable deployment of LLMs and NLP models for legal and clinical document processing.
Ensure model transparency, fairness, and defensibility in regulated environments.
Lead the design and management of data lakes, warehouses, and structured repositories integrating clinical, legal, and financial data.
Oversee development of ETL/ELT workflows and streaming pipelines from EHRs, incident reports, and claims systems.
Ensure data quality, lineage, and auditability across actuarial and compliance functions.
Build and maintain cloud-native platforms on Azure for scalable AI workloads.
Implement infrastructure-as-code (Bicep, Terraform), containerization (Docker), and orchestration (Kubernetes).
Integrate DevOps and MLOps practices to support continuous delivery and monitoring of AI-enabled features.
Partner with patient safety, marketing, underwriting, legal, actuarial, and compliance teams to align architectural decisions with business goals and regulatory mandates.
Mentor engineers and analysts on best practices in data architecture and responsible AI.
Evaluate emerging technologies to enhance risk modeling and provider engagement.
Contribute to the strategic direction of the Data and AI organization by evaluating new technologies, publishing internal whitepapers, and representing the team in cross-functional forums.
Mentor team across enterprise in leading best practices with the evolving technological landscape.
Foster a culture of innovation, compliance, and continuous learning.

Requirements

Advanced degree in Computer Science, Data Engineering, or related field
Bachelor’s or Master’s degree in Computer Science, Data Engineering, or related field (PhD a plus).
8+ years of experience in data architecture, AI/ML systems design, or cloud infrastructure, with at least 3 years in healthcare, insurance, or legal tech.
Deep expertise in cloud platforms (Azure preferred), data infrastructure (e.g., Snowflake, Databricks), and streaming frameworks (Kafka, Spark).
Strong experience with ETL/ELT, data governance, and batch/real-time processing.
Proficiency in Python, SQL, and infrastructure tools (Terraform, Docker, Kubernetes).
Familiarity with MLOps, model monitoring, and AI/ML lifecycle management in regulated environments.
Understanding of healthcare data standards (FHIR, HL7), insurance data models, and regulatory frameworks (HIPAA, NAIC, SOC 2).

Benefits

Competitive compensation
Incentive bonus plan
Outstanding career opportunities
Exceptional work environment
Medical, family and bereavement leave
Same-sex domestic partner benefits
Short- and long-term disability programs
Employee assistance program
Health, dental, and vision insurance
Health care tax-free spending accounts with a company match
401(k) and Roth IRA with company match, as well as catch-up plans for both
Vacation days, sick days, and paid personal days each calendar year (with vacation increases based on length of service)
Paid holidays each calendar year
Life and travel insurance
Tax-free commuter benefits
In-person and online learning opportunities
Cross-function career opportunities
Business casual work environment
Time off to volunteer
Matching donations to qualifying nonprofit organizations
Company-sponsored participation at non-profit events

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

data architectureAI/ML systems designcloud infrastructureETLELTdata governancepredictive modelingrisk scoringNLPmodel monitoring

Soft Skills

mentoringleadershipcollaborationinnovationcommunicationstrategic directioncontinuous learningbest practicescomplianceproblem-solving

Certifications

advanced degree in Computer Scienceadvanced degree in Data EngineeringPhD in related field