Member of Technical Staff, Applied AI Engineer
AI summary of the role
Edison Scientific is hiring an Applied AI engineer to build and maintain production AI agents for their AI scientist agent, Kosmos, which accelerates life sciences R&D.
What you’ll do
- Architect, implement, and maintain AI agents from prototype to production.
- Explore new agent architectures, prompting strategies, tool integrations, and evaluation frameworks with internal teams.
- Develop reusable infrastructure like agent skills, tool-use pipelines, and benchmarks.
- Spend ~30% time with R&D partners to understand workflows and test builds in real environments.
What you’ll bring
- 4+ years of professional software engineering experience with production systems.
- Experience building LLM-powered tools or applications (prompting, context engineering, agent architectures, evaluation).
- Strong engineering foundation in CS, software engineering, math, physics, data science, or related field.
- Proficiency in Python and/or TypeScript.
Technologies
LLM · Python · TypeScript · agent architectures · prompting · context engineering · evaluation frameworks · tool-use pipelines · benchmarking
Source and classification
Internal deployment & tooling · Evidence for this classification:
About us Edison Scientific builds and deploys AI scientist agents to accelerate science and the development of new medicines. We are an ambitious team run by scientists and engineers from leading institutions across biology, physics, chemistry, and AI. The Role We're looking for an Applied AI engineer to join the team responsible for building Edison's AI agents. This team owns the development and design of our AI scientist agent, Kosmos. You'll own the development and maintenance of production agents, prototype new capabilities with our internal science and engineering teams, and shape how our platform evolves. You'll spend some time with customers to understand real workflows and validate what you're building, but your primary focus is on the agents themselves – making them more capable, more reliable, and more useful across the life sciences. Responsibilities Architect,
More from the job description
About us Edison Scientific builds and deploys AI scientist agents to accelerate science and the development of new medicines. We are an ambitious team run by scientists and engineers from leading institutions across biology, physics, chemistry, and AI. The Role We're looking for an Applied AI engineer to join the team responsible for building Edison's AI agents. This team owns the development and design of our AI scientist agent, Kosmos. You'll own the development and maintenance of production agents, prototype new capabilities with our internal science and engineering teams, and shape how our platform evolves. You'll spend some time with customers to understand real workflows and validate what you're building, but your primary focus is on the agents themselves – making them more capable, more reliable, and more useful across the life sciences. Responsibilities Architect, implement, and maintain the AI agents that power Edison's platform, from prototype through production. Work with our internal science and engineering teams to explore new agent architectures, prompting strategies, tool integrations, and evaluation frameworks. Develop reusable infrastructure – agent skills, tool-use pipelines, benchmarks – that improves every agent on the platform. Spend time with R&D partners (~30%) to understand their workflows, test what you've built in real environments, and bring [... source excerpt omitted ...] internal research into product direction – help the team prioritize what to build next. Qualifications Typically, 4+ years of professional software engineering experience, with production experience shipping systems that real users depend on. Experience building LLM-powered tools or applications: prompting, context engineering, agent architectures, evaluation frameworks. Strong engineering foundation in Computer Science, Software Engineering, Mathematics, Physics, Data Science, or a related technical field. Proficiency in Python and/or TypeScript, with comfort picking up new tools and frameworks quickly. Able to work across engineering, science, and product teams. Comfortab
Employer postings · Data from · Sources