Agentic AI Engineer - Scientific Discovery
Software engineering role building AI agents, RAG systems, and LLM-powered research tools for computational drug discovery at a scientific research organization. Core stack is Python and generative AI; you take projects from prototype to production. Hybrid: 3 days/week in the NYC office; $250K–$600K base plus bonuses.
- Compensation
- $250K–$600K / yr
- Location
- New York, New York, United States
- Work setup
- Hybrid
- Seniority
- Not specified
- Employment
- Not specified
- Experience
- Not specified
- Category
- Ai engineering
- Posted
Skills
Must have
- Exceptional software engineering ability with a track record building complex production systems, infrastructure, or developer tools
- Strong Python experience
- Hands-on experience or serious technical depth in generative AI, AI agents, LLM applications, RAG, or adjacent AI systems
- Demonstrated ability to architect systems and carry projects from open-ended idea to production
- Strong computer science and software engineering fundamentals
- Exceptional record of academic, technical, research, or professional achievement
- Intellectual curiosity and ability to learn new technical and scientific domains quickly
Nice to have
- Scientific computing or research experience
- Exposure to computational chemistry, molecular science, or drug discovery workflows
Full description
Location: New York, NY
Work Model: Hybrid
Compensation: $250K to $600K base, plus sign-on and year-end bonuses
Overview
A well-established scientific research organization is standing up a new AI initiative at the intersection of agentic systems, generative AI, scientific computing, and drug discovery. The work is greenfield: rather than maintaining mature systems, the role will help define how AI agents, retrieval systems, and intelligent workflows are built and deployed for researchers working on hard problems in molecular science.
The position is a software engineering role first. It calls for someone who has built complex production systems and now wants to apply that ability to LLM applications, RAG architectures, and AI-assisted research tooling used directly by accomplished scientists and ML researchers. The role carries end-to-end ownership, from initial experimentation and prototyping through production-scale deployment.
The environment rewards technical depth and curiosity. The strongest candidates will be comfortable learning unfamiliar scientific domains quickly and translating emerging AI capabilities into reliable software that measurably increases researcher productivity.
What You'll Do
- Design, build, and deploy AI agents, retrieval systems, and RAG architectures that serve as everyday research tools
- Take ambitious ideas from ambiguous concept through prototype and into production at scale
- Build AI-powered systems that accelerate computational drug discovery and researcher workflows
- Develop data pipelines, feedback loops, automation, and AI-assisted development workflows
- Integrate new AI capabilities with complex scientific software and existing machine learning systems
- Collaborate closely with engineers, ML researchers, and scientists on technically demanding problems
What We're Looking For
- Exceptional software engineering ability with a track record of building complex production systems, infrastructure, or developer tools
- Strong Python experience
- Hands-on experience or serious technical depth in generative AI, AI agents, LLM applications, RAG, or adjacent AI systems
- Demonstrated ability to architect systems and carry projects from open-ended idea to production
- Strong computer science and software engineering fundamentals
- An exceptional record of academic, technical, research, or professional achievement
- Intellectual curiosity and the ability to learn new technical and scientific domains quickly