What You Will Do
This is a highly technical, hands-on engineering role focused on building practical AI solutions that solve real business problems. You’ll partner closely with actuaries, data scientists, software engineers, analysts, clinicians, and product leaders to identify opportunities where AI can improve our products, automate complex work, and help our team move significantly faster.
We’re looking for someone who loves building, experimenting, and learning. Excellent communication skills and a consultative mindset are a must. You should be equally comfortable evaluating the latest AI research, writing production-quality code, rapidly prototyping new ideas, and helping teammates understand how to use modern AI tools effectively.
This role offers the opportunity to join our team on a temporary basis. The position is expected to require a commitment of 20 hours per week for approximately 6 months. The duration of the position has the potential for extension based on performance and business needs.
AI Engineering
- Lead the design, architecture, testing, and deployment of production AI and machine learning solutions for the organization’s most complex and strategically important use cases.
- Build the reusable data and modeling infrastructure that lets the team develop and deploy new predictive models rapidly and repeatably.
- Encode the team’s existing modeling process into agentic AI workflows that can be reused across many different prediction problems.
- Use agentic AI to reproduce established predictions (for example, projected medical costs), then extend the same data and process to new predictions (for example, likelihood of an emergency department visit).
- Develop LLM-enabled applications, agentic workflows, and retrieval-augmented generation (RAG) systems.
- Evaluate foundation models and determine the right technologies for each use case, taking into consideration relevant constraints (e.g., IT security requirements).
- Build AI services and APIs that integrate into existing software products.
- Optimize AI systems for quality, reliability, latency, and cost.
Software Engineering
- Define and exemplify high standards for production software engineering in AI-enabled systems, including maintainability, scalability, testing, and operational excellence.
- Integrate AI capabilities into existing applications and workflows.
- Build automated testing, evaluation, and deployment pipelines for AI systems.
- Work closely with the team to ensure AI solutions are maintainable and scalable.
Applied AI Innovation
- Stay current with rapidly evolving AI technologies, research, and tooling.
- Quickly prototype promising ideas and evaluate their practical business value.