AI Systems Quality Engineer

About Us

Abacus Insights is transforming how data and AI work for health plans. Our mission is simple: make healthcare data usable, so the people responsible for care and cost decisions can act faster, with confidence.

As the AI and Data Platform for Payer Intelligence, we help health plans break down data silos to create a single, trusted data foundation. That foundation powers better decisions—so plans can improve outcomes, reduce waste, and deliver better experiences for members and providers alike. Backed by $100M from top investors, we're tackling big challenges in an industry that's ready for change. Our platform enables GenAI use cases by delivering clean, connected, and reliable healthcare data to support automation, prioritization, and decision workflows—and it's why we are leading the way.

Our innovation begins with people. We are bold, curious, and collaborative—because the best ideas come from working together. We embrace the thoughtful use of AI and automation to drive innovation and efficiency, and we look for individuals who are curious and adaptable—those excited to leverage emerging technologies to enhance how we work—while keeping human insight, connection, and our clients at the center of every decision.

Ready to make an impact? Join us and let's build the future together.

About the Role

At Abacus Insights, we’re building AI‑powered platforms that sit at the center of critical healthcare decisions—where reliability, correctness, and trust matter as much as innovation. As our use of agentic, LLM‑driven systems scales, ensuring these systems behave safely and predictably in real‑world environments isn’t optional—it’s foundational. 

The Senior AI Systems Quality Engineer plays a critical role in making our AI systems production‑ready, operable, and trustworthy. This is not a traditional QA role. Instead, you’ll help define how quality is engineered into agentic systems from the very beginning—embedding guardrails, evaluation signals, and safe‑failure behavior directly into how these systems are designed, built, and deployed. In this role, you will also help design and own an AI testing platform that operates natively within our Databricks Medallion architecture—leveraging tools like MLflow to enable evaluation, lineage, traceability, and auditability at scale. This is a platform-oriented role, focused on establishing repeatable, scalable quality practices rather than point-in-time validation.

You’ll partner closely with AI Engineers, platform teams, and delivery stakeholders to design custom evaluation frameworks, validation pipelines, and automated testing harnesses that reflect how agentic systems behave in production. You’ll focus on validating orchestration logic, managing non‑deterministic behavior, and ensuring AI systems degrade safely under uncertainty, scale, and failure.