Architecture Senior Advisor AI Principal

Location: Remote

Job Description
Define and execute enterprise-wide Data AI Strategy, aligned with business and leadership.
Partner with executive leadership to identify and prioritize AI use cases that deliver measurable value
Establish a roadmap for Generative AI adoption, LLM deployment, and Responsible AI governance.
Serve as a thought leader across AI, ML, Data Engineering, and Business Transformation domains.
Design and prototype AI/ML and GenAI solutions using frameworks such as PyTorch, TensorFlow, LangChain, Hugging Face, and Vertex AI / Azure AI.
Drive end-to-end architecture from data ingestion and feature engineering to model deployment and monitoring.
Mentor data scientists, MLOps engineers, and solution architects in advanced modeling, GenAI pipelines, and prompt optimization.
Evaluate and integrate enterprise and open-source AI platforms to accelerate innovation.
Define data modernization roadmap encompassing data fabric, metadata management, and data quality frameworks.
Partner with enterprise architecture to ensure data accessibility, interoperability, and AI-readiness.
Lead initiatives around data democratization and AI-native platform enablement (including RAG, vector databases, and feature stores).
Champion the convergence of Data, AI, and Analytics platforms for unified intelligence delivery.
Work closely with Product, Clinical, PBM, and Engineering teams to embed AI capabilities within business workflows.
Partner with external vendors and hyperscalers (AWS, Azure, Google Cloud) to co-develop scalable AI solutions.
Communicate complex AI strategies clearly to senior leadership, stakeholders, and non-technical partners. Qualifications Required
10+ years of experience in Data Science, AI, or Enterprise Data Strategy, with at least 5+ years in leadership/principal roles.
Strong hands-on expertise in machine learning, GenAI, NLP/LLM development, and MLOps.
Proven ability to build and scale AI Centers of Excellence (CoE) and align technical execution with enterprise strategy.
Proficiency with Python, SQL, cloud-native AI platforms, and modern data stack (Databricks, Snowflake, Airflow, MLflow, etc.).
Demonstrated success influencing senior executives and leading cross-functional AI transformations. Desired:
Experience with responsible AI, governance frameworks, and regulatory compliance (HIPAA, PHI).
Experience implementing agentic AI or autonomous analytics frameworks.
Track record of AI commercialization, IP creation, or research contributions.
Good to have understanding of Insurance, PBM, Healthcare data domains
Good to have understanding and working experience in End-user/Contact Center technology verticals

Education:
Master s or Bachelor s in Computer Science, Data Science, or related field.