Senior AI Machine Learning Engineer

What you'll do

• Lead day-to-day engineering for the predictive model portfolio, including pricing and underwriting models.
• Build and maintain AI/ML components and data pipelines for various business workflows.
• Translate approved solution designs into tested, reliable production code and workflows.
• Build generative AI and agentic AI solutions, including prompt orchestration and RAG patterns.
• Develop and operate batch and near-real-time data pipelines for model training and inference.
• Deploy and sustain production AI services, APIs, and workflows in AWS and GCP environments.
• Own implementation quality through code reviews, unit testing, documentation, and incident response.
• Guide and mentor junior engineers by reviewing code and explaining model/data pipeline patterns.

What we're looking for

• Bachelor’s degree in a related field or 6+ years of equivalent experience in software, data, or ML/DevOps engineering.
• Master's degree in computer science, engineering, information technology, MIS, data science, or a related discipline (preferred).
• Strong hands-on expertise in Python, SQL, SDLC practices, Git-based development, automated testing, and production-grade code delivery.
• Experience deploying and operating data, AI, or ML workloads in AWS and GCP environments.
• Experience with ML engineering concepts including feature pipelines, model training, batch scoring, inference services, and drift detection.
• Ability to lead implementation work, guide junior engineers, and manage multiple deliverables with limited day-to-day direction.
• Experience in insurance, employee benefits, pricing, underwriting, or policy lifecycle analytics (preferred).
• Experience with generative AI, agentic AI, RAG, or orchestration tools like Airflow and Vertex AI Pipelines (preferred).