AI Therapy Architect & Research Engineer

Monograph; San Francisco (CA); On-site; USD 180,000 - 240,000; Full time

Job summary

Monograph is seeking an experienced AI/ML engineer to design, train, and deploy the AI therapy system. You will collaborate with clinicians, product, and engineering to improve therapy conversations, safety, and model quality. The role emphasizes building robust eval stacks and production-ready pipelines.

You will iterate quickly, balance quality and speed, and translate clinical requirements into scalable model and system changes for the product.

Qualifications

• Experience with large language models, fine-tuning, data design, and model selection.
• Ability to evaluate conversations, metrics, transcripts, and to form grounded hypotheses.
• Production-level software engineering experience in AI systems.
• Ability to design and manage data pipelines for training and evals.
• Strong scientific mindset with hypothesis testing and data analysis.
• Excellent prioritization to maximize company value and avoid scope creep.
• Efficient, fast delivery with iterative learning and minimal over-engineering.
• Clear collaboration with clinicians, product, and engineering.

Responsibilities

• Own AI system end-to-end, from data to production deployment and monitoring.
• Improve AI therapy quality and evaluation stacks with robust experiments.
• Productionize models and pipelines, manage training jobs, deployment, and rollback.
• Encode clinical guidelines into prompts and safety filters.
• Shape a focused R&D roadmap and run high-quality experiments.
• Collaborate with clinicians, product, and engineering to integrate AI capabilities.

Skills

LLM depth

Applied ML

Code quality

Data engineering

Scientific mindset

Prioritization

Fast delivery

Strong communication

Job description

Monograph is seeking an experienced AI/ML engineer to design, train, and deploy the AI therapy system. You will collaborate with clinicians, product, and engineering to improve therapy conversations, safety, and model quality. The role emphasizes building robust eval stacks and production-ready pipelines.

You will iterate quickly, balance quality and speed, and translate clinical requirements into scalable model and system changes for the product.