OpenLoop is the white label telehealth platform trusted by 400+ virtual care brands. Clinicians, pharmacy, diagnostics, AI — all under your brand. Backed by Techstars.
About the role
OpenLoop is building the future of healthcare infrastructure. We are hiring for this role at the Senior, Staff and Senior Staff levels. Apply once; we will calibrate level during the process based on the scope you have carried and the depth you bring, not on years alone. Ship Production Agents: Build and run LLM-based agents and assistants that real users depend on, not prototypes. Found on 1752vc Careers, the job board for startup and VC roles.
What they're looking for
- Bachelor's degree in Computer Science, Engineering, or a related technical field
- Proven Engineering Experience: 5 to 15+ years of software engineering experience
- Production LLM Experience: Hands-on experience building and running LLM-based systems in production that real users relied on, not only demos, prototypes or personal projects. Senior Staff candidates typically bring 2+ years
- Evaluation Rigor: Experience measuring whether an AI system works with evaluation data, rather than "it seemed to work."
- Engineering Fundamentals: Strong production engineering across testing, debugging, services, APIs, deployment and on-call
- Data & Security Fluency: Experience handling sensitive data with a security-first mindset
More about this role
OpenLoop was co-founded by CEO, Dr. Jon Lensing, and COO, Christian Williams, with the vision to bring care anywhere. Our telehealth support solutions are thoughtfully designed to streamline and simplify go-to-market care delivery for companies offering meaningful virtual support to patients across an expansive array of specialties, in all 50 states.
OpenLoop is building the future of healthcare infrastructure. We are hiring for this role at the Senior, Staff and Senior Staff levels. Apply once; we will calibrate level during the process based on the scope you have carried and the depth you bring, not on years alone.
Ship Production Agents: Build and run LLM-based agents and assistants that real users depend on, not prototypes.
Agent Runtime & Orchestration: Build how agents run, call tools, hold context and hand off work, including failure handling, retries, timeouts and sandboxing.
Evaluation: Build evaluation sets, test harnesses, regression tests and AI-graded evals so the team can show "this got better" with numbers and catch regressions before users do.
Model Access & Operations: Work across multiple model providers, manage version upgrades and plan fallbacks for when a...
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