Agentic AI Lead for Scientific Workflows

Monte Rosa Therapeutics, Inc.; Basel; Hybrid; CHF 180,000 - 260,000; Full time

Job summary

Monte Rosa Therapeutics, Inc. is seeking an accomplished technical leader to define and build our agentic AI strategy. This hands-on role drives architecture across discovery, translational science, and clinical development, delivering production-ready AI agents used by scientists daily.

You will own the roadmap, supervise data/knowledge infrastructure, and mentor a growing AI team, balancing scientific impact with scalable engineering and responsible deployment.

Qualifications

• PhD in ML, CS, stats, bioinformatics, physics, engineering or quantitative field.
• Proven track record as applied ML scientist/engineer with execution.
• Experience deploying LLM/agentic systems in real workflows.
• Strong Python and production-grade development skills.

Responsibilities

• Own vision, architecture and roadmap for agentic AI across discovery to commercialization.
• Identify high-value workflows and redesign around AI agents from first principles.
• Build data and knowledge layers; integrate diverse data sources.
• Develop connectors, APIs, and retrieval systems for reliable agent use.
• Deploy secure, auditable agentic systems with human-in-the-loop oversight.
• Establish evaluation frameworks: benchmarks, provenance, latency, cost tracking.
• Partner with scientists to turn needs into products and adopted workflows.
• Drive adoption of agentic-first practices through demos and training.
• Track advances in foundation and multimodal models and translate to internal use.
• Define outcome-based success measures and mentor the AI team.

Skills

Agentic AI systems

LLM deployment

Production engineering

Python development

Knowledge graphs

RAG architectures

Education

PhD in ML or related field

Tools

APIs

Containers

Cloud deployment

Observability

Job description

Monte Rosa Therapeutics, Inc. is seeking an accomplished technical leader to define and build our agentic AI strategy. This hands-on role drives architecture across discovery, translational science, and clinical development, delivering production-ready AI agents used by scientists daily.

You will own the roadmap, supervise data/knowledge infrastructure, and mentor a growing AI team, balancing scientific impact with scalable engineering and responsible deployment.