AI Engineering Lead

Role overview

An early-stage healthcare AI company is hiring a hands-on engineering lead to evolve a live primary care platform into a fully agentic system. The role focuses on architecting multi-modal patient communication, intelligent care coordination, and clinical system integrations, with a direct feedback loop between what is built and what happens in patient care. The position reports to the VP of Product and Engineering, is remote within the United States, and includes early-stage equity.

Responsibilities

- Architect and build agentic AI systems covering orchestration, memory, tool use, and multi-step reasoning - Design and operate the multi-modal communication layer, including a voice AI pipeline and asynchronous channels such as SMS - Lead EMR integration work that connects the platform to clinical data using standards like FHIR and HL7 - Build evaluation frameworks, monitoring, and graceful-failure handling for AI outputs in a clinical context - Develop scalable, privacy-preserving backend infrastructure - Run code review, manage dependencies, and participate in on-call rotation and incident response - Collaborate closely with the product team using AI-native workflows to accelerate shipping

Requirements

- Bachelor's degree in Computer Science, Software Engineering, or a closely related technical field - Five or more years of professional software engineering experience, including at least two years building and operating AI or machine learning systems in production - Hands-on LLM application experience, including orchestration, retrieval-augmented generation, tool use, function calling, and multi-step reasoning - Strong backend fundamentals in Python and/or TypeScript, including APIs, async and event-driven systems, and data pipelines - Experience deploying and operating services on AWS, GCP, or Azure, including CI/CD, containerization, and infrastructure as code - Experience handling sensitive or regulated data, including encryption, role-based access control, and audit logging - Clear written and verbal communication for working directly with clinicians and non-technical stakeholders - Self-directed, proactive, and authorized to work in the United States

Nice to have

- Master's or doctoral degree in Computer Science, AI, Machine Learning, or a related field - Healthcare data and EMR integration experience with FHIR, HL7v2, and platforms such as Epic, athenahealth, or eClinicalWorks - Working knowledge of HIPAA engineering practices and experience under SOC 2 or HITRUST - Real-time voice AI experience, including speech recognition and synthesis, telephony (Twilio, LiveKit, SIP), and low-latency streaming pipelines - Prior experience building evaluation and monitoring frameworks for non-deterministic model output - Prior founding or lead engineer experience at an early-stage startup - Cloud or security certifications such as AWS Solutions Architect, AWS Security Specialty, or CISSP

Benefits and work setup

- Remote, full-time role open to US-based applicants only - Compensation includes early-stage equity - Small, mission-driven team focused on building infrastructure for continuous patient care between visits