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Applied AI Scientist (Clinical AI Agents)
Hybrid | NY
A fast-growing AI-native technology company is hiring Applied AI Engineers to help build and deploy the next generation of agentic AI systems.
This is not a traditional machine learning role.
The team is looking for engineers who are excited about building real-world AI products, designing agent workflows, experimenting with emerging tools, and shipping systems that create measurable business impact.
Successful candidates will work on complex, multi-step AI systems that reason, retrieve information, make decisions, interact with tools, and automate workflows that previously required significant human effort.
What You’ll Work On
- Design and build production-grade AI agents
- Develop multi-step workflows involving reasoning, retrieval, tool use, memory, routing, and verification
- Build systems that leverage LLMs, RAG, structured outputs, and agent orchestration frameworks
- Create evaluation frameworks, benchmarks, and feedback loops to improve agent performance
- Prototype new capabilities quickly and iterate based on real-world usage
- Partner closely with engineering, product, and domain experts to solve complex operational problems
- Turn cutting-edge AI capabilities into reliable production systems
Ideal Background
Strong candidates may come from either a software engineering or applied AI background.
Experience with some combination of the following is highly valuable:
- AI Agents
- LLM Applications
- Retrieval-Augmented Generation (RAG)
- Tool Calling
- Prompt Engineering
- LangGraph
- LangChain
- Agent Frameworks
- Evaluation Systems
- Workflow Automation
- Python Backend Development
What The Team Values
- Strong builders who ship quickly
- Product-oriented thinking
- Curiosity around emerging AI tools and frameworks
- Comfort operating in ambiguity
- Ability to learn and adapt rapidly as the ecosystem evolves
- Focus on outcomes rather than research for research’s sake
Examples of Relevant Experience
- Building AI copilots or assistants
- Designing agent workflows
- Developing AI-powered internal tools
- Building evaluation and monitoring systems for LLM applications
- Creating retrieval and reasoning pipelines
- Shipping AI products that users interact with daily
Why Join?
The company is investing heavily in AI and views agentic systems as a core part of its future product strategy.
Engineers on this team have significant ownership, move quickly, and work directly on products that are already delivering value at scale. This is an opportunity to help define how modern AI systems are built, deployed, and improved in production environments.
If you’re the type of person who constantly experiments with new AI tools, has strong opinions on agent frameworks, and enjoys turning cutting-edge capabilities into useful products, this is likely worth a conversation.
