Partner with embedded Product Managers to interpret business needs, prototypes, and early-stage AI builds
Take Product Manager-created concepts or prototypes and evolve them into production-ready AI applications
Design, build, and deploy end-to-end AI solutions, from refinement through launch
Develop applications using modern AI tooling, including Front-end builders (e.g., Replit, cloud-based development environments)
Hosting and deployment platforms (e.g., Vercel)
Internal AI platforms and services LLM APIs and orchestration frameworks
Manage code and collaboration workflows using GitHub (version control, branching, pull requests, CI/CD practices)
Evaluate and implement the most appropriate LLM models and architectures based on use case
Enhance and scale AI "co-workers" and workflow automation tools across business functions
Collaborate across internal teams (Marketing, Finance, HR) and external business lines (Employee Benefits, Wealth & Retirement, Financial Services)
Ensure solutions meet enterprise standards for scalability, security, and performance
Continuously improve existing AI solutions through iteration, optimization, and feedback
Stay current on emerging AI technologies and introduce new tools and capabilities into the ecosystem

Experience building and deploying AI-powered applications or prototypes
Strong familiarity with modern LLM ecosystems, including Prompt engineering and model behavior Model selection and tradeoffs (e.g., GPT, Claude, open-source models) Architectures such as RAG, agents, and workflow orchestration
Experience working across a full-stack AI toolchain, including front-end, backend, and deployment
Hands-on experience with Vercel (or similar platforms) for hosting and deployment
Proficiency with GitHub for version control and collaborative development workflows
Ability to take loosely defined or partially built solutions and turn them into scalable applications
Strong problem-solving skills and comfort working with ambiguity
Proven ability to learn new tools and technologies quickly in a rapidly evolving space
Preferred Bachelor’s degree
familiarity with software engineering concepts
Exposure to or experience with product management concepts, including working with requirements and user needs
Experience working with APIs, cloud services, and modern development environments
Familiarity with enterprise application development and deployment
Understanding of AI governance, data privacy, and security considerations.

AI Builder

Key skills