AI Engineer (Healthcare)

Location: San Francisco, United States; On-site

Company

hirify.global develops a primary care app that combines medical records, AI, and real doctors to provide personalized healthcare and prescriptions.

What you will do

• Build and operate AI and data systems supporting AI-driven primary care.
• Develop AI agent workflows with multi-step clinical reasoning, tool use, guardrails, fallback logic, and escalation paths.
• Improve medical knowledge bases, retrieval systems, citations, search relevance, and data lineage.
• Rebuild clinical data pipelines and create curated training and evaluation datasets with strong integrity and traceability.
• Build real-time voice and video AI capabilities for clinical intake, triage, and follow-up conversations.
• Develop observability, analytics, model monitoring, and evaluation systems covering quality, latency, safety, usage, and drift.

Requirements

• Strong programming skills, preferably Python, and comfort working across schema design, infrastructure, and production debugging.
• Experience building production systems that power AI or ML workflows and shipping AI-powered product features with LLM APIs and prompt engineering.
• Experience with system refactors, schema migrations, data infrastructure simplification, PostgreSQL, and AWS.
• Experience with model training or fine-tuning, data curation, annotation workflows, hyperparameter tuning, and model evaluation.
• Ability to design systems balancing correctness, observability, performance, and compliance-grade visibility.

Nice to have

• Experience with PyTorch, Hugging Face, vLLM, Axolotl, RLHF, DPO, or other alignment and preference-tuning techniques.
• Experience building AI agents with tool use and multi-step reasoning, or LLM retrieval systems using RAG, vector search, and grounding.
• Familiarity with FastAPI, SQLAlchemy, DuckDB, Temporal, ClickHouse, Valkey, Sentry, Langfuse, Docker, or ECS.
• Experience with real-time voice AI, speech models, computer vision, medical imaging, or multimodal systems.

Culture & Benefits

• Work on a small, autonomous engineering team with direct influence on patient care.
• Collaborate closely with engineers, clinicians, and AI researchers.
• Work in a generalist environment with changing priorities based on user needs, clinician feedback, safety issues, and system reliability.
• Expected progress includes shipping reliably in 30 days, owning a meaningful system in 60 days, and independently driving a roadmap slice in 90 days.

Hiring process

• Quick introductory call followed by a short technical screen.
• One deeper technical interview and a team chat.
• References and offer; the process usually takes approximately 7–10 days.