Senior AI Engineer

Recruiting From Scratch•San Francisco, CA

7d•Hybrid

About The Position

The company is building AI-powered clinical workflows that eliminate administrative burden for home health clinicians. Already deployed across thousands of clinicians serving tens of thousands of patients daily, the platform automates documentation, streamlines workflows, and allows healthcare providers to spend more time delivering patient care. Founded by experienced AI researchers and operators with backgrounds in large-scale AI systems, the company has rapidly gained traction within healthcare and recently completed a Series A financing round to support aggressive growth. As the first dedicated AI hire, this Senior AI Engineer will own the intelligence layer of the platform, building the systems responsible for model accuracy, evaluation, inference, monitoring, and production AI workflows. This is a rare opportunity to join an early-stage healthcare AI company with real-world deployment, proprietary clinical datasets, and significant ownership over the future of the AI organization.

Requirements

7+ years of software engineering experience with significant AI/ML depth
Experience training or fine-tuning open-source LLMs in production environments
Experience building production AI systems rather than research-only projects
Experience at Seed to Series B startups
Experience designing evaluation frameworks and model monitoring systems
Demonstrated ownership of AI products from experimentation through deployment
Founding Engineer or early AI hire experience preferred
Healthcare AI experience strongly preferred
Experience building systems used by real customers in high-accuracy environments
Strong Python engineering skills
Experience fine-tuning open-source models such as LLaMA, Mistral, or similar
Deep understanding of model evaluation and benchmarking methodologies
Experience with LoRA, PEFT, Hugging Face, or related fine-tuning frameworks
Experience building inference infrastructure and model-serving systems
Experience with agentic systems, orchestration, and tool usage frameworks
Experience with monitoring, observability, and production AI operations
Familiarity with vector databases, retrieval systems, and RAG architectures
Strong system design and architecture fundamentals
Degree in Computer Science, Machine Learning, AI, or related technical field
High ownership mentality
Strong communication and collaboration skills
Ability to operate independently
Comfortable working in ambiguity
Strong product judgment
Startup mindset and bias toward execution
Passion for healthcare impact

Nice To Haves

Graduate degree (MS or PhD) in AI, NLP, ML, or related field strongly preferred
Healthcare AI startups
Clinical documentation AI companies
Voice AI and healthcare NLP platforms
Early-stage venture-backed startups
Founding AI Engineer backgrounds
Teams deploying production LLM systems
Organizations focused on model evaluation and accuracy

Responsibilities

Train and fine-tune open-source foundation models using proprietary healthcare datasets
Build evaluation frameworks, benchmarks, and monitoring systems that continuously improve model quality
Design metrics, feedback loops, and accuracy measurement systems tied to real-world clinical outcomes
Build scalable and cost-efficient inference infrastructure for production AI systems
Develop agentic AI workflows that clinicians rely on daily
Improve model accuracy, latency, reliability, and observability across production environments
Partner closely with founders and leadership on AI strategy and technical direction
Prototype new AI capabilities and rapidly transition them into production systems
Stay current on frontier AI research and incorporate new techniques into production workflows
Help establish the long-term AI roadmap and eventually build and mentor the AI team