Lead AI Engineer (Scientific Multi Agent Systems)

Location:

Remote: USA, Canada, Europe or UK

Responsibilities:

  • Design and build multi-agent systems that integrate scientific tools, computational workflows, MCP-compatible services, APIs, and cheminformatics libraries such as RDKit. 
  • Build containerized deployment pipelines (Docker) with proper observability (Langfuse), logging, and lifecycle management. 
  • Collaborate on the development of agent evaluation frameworks, including automated testing, benchmarking, and performance monitoring. 
  • Develop data preparation and engineering pipelines across structured, semi-structured, and unstructured sources, working alongside the data team's stack (Snowflake, Airflow, DBT, PostgreSQL, Oracle). 
  • Contribute to CI/CD workflows and maintain code quality through code reviews, modular design practices, and technical documentation. 
  • Follow architecture, security, and engineering patterns established by the team. 

What we expect:

  • Strong Python software engineering. 
  • Experience building applications based on LLMs, tool-calling, and agent frameworks. 
  • Experience developing multi-agent or workflow-oriented AI systems. 
  • Experience with evaluation frameworks, automated testing, and performance benchmarking. 
  • Docker and containerized application development expertise. 
  • Comfortable working with databases and data engineering workflows. 
  • Ability to collaborate in a cross-functional scientific environment. 
  • Availability to work until at least 1:00 PM EST. 

Nice to have:

  • Langfuse or another AI observability platform experience. 
  • Snowflake Cortex and/or Amazon Bedrock experience. 
  • AWS ECS/Fargate deployment experience. 
  • Data engineering stack experience: Snowflake, Airflow, DBT, Oracle. 
  • GitLab-based development practices experience. 
  • Experience in drug discovery / cheminformatics: RDKit, chemical structure analysis, assay data interpretation, scientific data visualization, retrieval over structured and unstructured research sources. 

We offer:

  • Competitive compensation
  • Flexible working hours
  • Continuous education, mentoring, and professional development programs
  • A team with an excellent tech expertise
  • Contract through the end of the year, with a possible extension based on project needs and performance.
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If you don't see an open position that suits your skills stack and/or professional background but you are interested in working with us — please send your CV to career@quantori.com. We will try to find something special and interesting for you!
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