Note: The job is a remote job and is open to candidates in USA. Prosperity Life is seeking an Artificial Intelligence Engineer to support the development, deployment, and optimization of AI-driven solutions for their business lines. The role involves building models and data-driven tools to enhance operations and improve customer experiences while contributing to the company's digital transformation.

Responsibilities

• Applied Machine Learning: Experience building and deploying ML models, including regression, classification, recommendation engines, or predictive analytics
• NLP & Generative AI Foundations: Understanding of text analytics, large language models, and conversational AI tools
• Programming & Automation: Proficiency with Python, SQL, and common data science libraries (e.g., Pandas, Scikit-Learn, TensorFlow, PyTorch)
• Life & Annuity Domain Knowledge: Familiarity with product structures, customer journeys, and distribution processes in life insurance and annuities
• Data Analysis & Feature Engineering: Ability to clean, prepare, and analyze structured and unstructured data
• Model Evaluation & Monitoring: Understanding of model accuracy, drift, explainability, and continuous improvement approaches
• Business Collaboration: Ability to translate business needs into technical solutions and communicate complex concepts clearly
• Problem-Solving: Strong analytical mindset and creativity in identifying automation and AI opportunities
• Adaptability: Comfort learning new tools, working in an evolving AI landscape, and supporting emerging business demands
• Tool Proficiency: Experience with cloud platforms (AWS, Azure, GCP), version control (Git), and MLOps or workflow-automation tools is a plus

Skills

• Bachelor's degree in Computer or Data Science, Engineering, Mathematics, or related field
• 1–5 years of experience in AI, machine learning, data science, or applied analytics
• Experience working with Python, SQL, and common ML frameworks
• Understanding of life insurance and annuity products—or strong willingness to learn quickly
• Strong communication and collaboration skills supporting cross-functional teams
• Ability to translate complex data concepts into actionable business recommendations
• Curiosity, initiative, and a growth mindset—eager to explore emerging AI technologies
• Applied Machine Learning: Experience building and deploying ML models, including regression, classification, recommendation engines, or predictive analytics
• NLP & Generative AI Foundations: Understanding of text analytics, large language models, and conversational AI tools
• Programming & Automation: Proficiency with Python, SQL, and common data science libraries (e.g., Pandas, Scikit-Learn, TensorFlow, PyTorch)
• Life & Annuity Domain Knowledge: Familiarity with product structures, customer journeys, and distribution processes in life insurance and annuities
• Data Analysis & Feature Engineering: Ability to clean, prepare, and analyze structured and unstructured data
• Model Evaluation & Monitoring: Understanding of model accuracy, drift, explainability, and continuous improvement approaches
• Business Collaboration: Ability to translate business needs into technical solutions and communicate complex concepts clearly
• Problem-Solving: Strong analytical mindset and creativity in identifying automation and AI opportunities
• Adaptability: Comfort learning new tools, working in an evolving AI landscape, and supporting emerging business demands
• Tool Proficiency: Experience with cloud platforms (AWS, Azure, GCP), version control (Git), and MLOps or workflow-automation tools is a plus

Company Overview