Agent Engineer for AI Scientist Agents (Life Sciences)

Edison Scientific

San Francisco (CA)

On-site

USD 175,000 - 240,000

Full time

6 days ago
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Benefits offered by this job

Competitive salary
Equity
Healthcare coverage
Parental leave
Mental health support
Wellness stipend
Lunch provided
Team off-sites

Job summary

Edison Scientific is seeking an Agent Engineer to design, build, and maintain production AI agents that power the Kosmos platform. You will prototype new capabilities with internal science and engineering teams and validate workflows with real customers, while ensuring reliability and usefulness across life sciences.

You’ll work across engineering, science, and product teams, translating insights into direction, and shaping how the platform evolves with scalable agent architectures and

Qualifications

  • 4+ years of professional software engineering experience.
  • Experience building LLM-powered tools or applications.
  • Strong foundation in CS/SE/Math/Physics/Data Science.
  • Proficiency in Python and/or TypeScript.
  • Able to work across engineering, science and product teams.
  • Comfortable building from scratch and navigating ambiguity.

Responsibilities

  • Architect, implement, and maintain AI agents from prototype to production.
  • Collaborate with science and engineering teams to explore new architectures.
  • Develop reusable infrastructure – agent skills, tool-use pipelines, benchmarks.
  • Spend ~30% with R&D partners to test workflows and gather insights.
  • Translate field insights into product direction and priorities.

Skills

Python
TypeScript
LLM-powered tools
Prompting
Context engineering
Agent architectures
Evaluation frameworks

Job description

Edison Scientific is seeking an Agent Engineer to design, build, and maintain production AI agents that power the Kosmos platform. You will prototype new capabilities with internal science and engineering teams and validate workflows with real customers, while ensuring reliability and usefulness across life sciences.

You’ll work across engineering, science, and product teams, translating insights into direction, and shaping how the platform evolves with scalable agent architectures and

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