Role overview
Why AAA Life
AAA Life is a respected and trusted American brand that has been focusing on Life Insurance and Annuity Products since 1969. At AAA Life we have over 1.8 million policies where we take pride in earning the trust of our policyholders who understand our promise to be there for them – and their families – when we’re needed most. By joining the AAA Life team, you are joining a company that genuinely cares about helping each other, with a devotion to protect the lives of those around us. We embrace a diverse, equitable, inclusive culture where all associates can feel a sense of belonging and use their unique talents and perspective to influence, innovate, motivate, and thrive.
At AAA Life, we are building a future-focused team using AI and automation to transform life insurance operations. If you're driven by meaningful work and want to deliver solutions that matter to millions of members, this is your opportunity.
How You’ll Work
Work Solution: Hybrid (Tuesday- Thursday)
Relocation Eligibility: Available
Responsibilities
- Design and implement intelligent systems using Generative AI, Retrieval-Augmented Generation (RAG), and Agentic AI to enhance operational efficiency and decision-making.
- Develop AI agents that assist internal teams (e.g., Claims, Underwriting, Member Services) with tasks like summarization, document processing, and knowledge retrieval.
- Partner with strategic vendors and platform providers to explore and integrate enterprise-grade GenAI capabilities into AAA Life’s ecosystem.
- Translate business problems into practical AI solutions, leveraging internal data and LLMs to create scalable tools.
- Implement and refine MLOps practices to support the deployment and monitoring of AI agents and services.
- Collaborate with stakeholders across operations, IT, and automation to align AI initiatives with business goals.
- Mentor junior engineers and advocate for best practices in responsible, sustainable AI implementation.
- Bachelor’s degree in a quantitative discipline (Computer Science, Mathematics, etc.).
- 1-3 years of experience working in a data science or ML engineering role.
- Understanding of basic MLOps principles and software engineering best practices.
Preferred qualifications
- Domain experience in Finance or Insurance.
- Strong proficiency in Python and familiarity with machine learning frameworks.
- Ability to perform data wrangling, exploratory analysis, and model validation.
- Clearly and effectively communicate complex ideas across multiple teams and varying levels of technical understanding.