We're looking for an AI Applied Researcher to join our growing team and help push the boundaries of how we build and improve our AI systems. This is a highly technical, research-driven role — you'll be the in-house expert on what's new in AI and how we can apply it. You'll run structured experiments to evaluate and improve our AI architecture, then hand off clear findings to the product engineering team to build into production.
This hire will also serve as our go-to prompting expert, helping the agent platform team tackle their toughest problems and level up the quality of their work. This is not a customer-facing role — you'll be operating behind the scenes, supporting the teams building our core product.
If you're energized by hard problems, love staying ahead of the curve in AI, and want your work to have real product impact — we'd love to hear from you!
Design and run structured experiments to evaluate new AI approaches in a development/prototype environment
Take a scientific approach — produce clear findings with evidence that supports which approach is better
Stay current on the latest AI research and bring relevant ideas to the team for exploration
Act as the team's expert prompter, reviewing and improving prompts written by the agent platform team
Step in on the hardest prompting challenges when iterations aren't landing
Help the team become more productive by unblocking complex prompting problems quickly
Translate experimental findings into clear reports that the product engineering team can act on
Identify opportunities to improve how our AI works at a foundational level
Collaborate closely with engineering leads to align on what experiments to prioritize
2+ years of experience with a PhD; will consider candidates without a PhD at 4+ years of relevant experience
Strong hands-on experience with LLMs and generative AI (not traditional ML/deep learning)
Proven ability to design and run AI experiments — not just build to spec, but explore and problem-solve independently
Expert-level prompting skills with real examples of improving AI outputs
Ability to take a high-level business problem and design creative AI architectures to solve it
Strong written communication — you'll be producing research reports and documentation regularly
PhD in a relevant field (especially with LLM-focused research)
Startup experience — you're used to wearing multiple hats and moving fast
Familiarity with agentic AI systems, multi-step planning, or adaptive decision-making architectures
Experience reading and applying findings from AI research papers
Base salary: $125,000 - $160,000
Equity: Meaningful ownership in a fast-growing healthtech startup
Hello Patient is transforming healthcare communication through advanced conversational AI. Our founding team spent 3.5 years scaling Carbon Health's technology during hypergrowth, where we saw firsthand how much clinical time gets wasted on basic communication—great clinicians buried in admin work, patients stuck in phone tag.
Our AI platform proactively engages patients through perfectly timed calls and texts, resolving complex interactions end-to-end—from scheduling to billing to retention. Built with security and compliance at its core, our technology integrates with existing healthcare infrastructure to deliver 24/7 patient engagement.
Backed by Scale and 8VC, we're building the future of healthcare communication, one conversation at a time.
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