Senior AI Engineer - Agentic Systems and LLM
New
J
JobgetherArtificial intelligence
100% remote within the United States.Full-TimeSenior
Salary60 USD per hour
Apply NowOpens the employer's application page
Job Details
- Experience
- 2–3 years of hands-on experience developing and implementing agentic AI workflows.
- Required Skills
- PythonPrompt EngineeringLangChain
Requirements
- Have 2–3 years of hands-on experience developing and implementing agentic AI workflows.
- Demonstrate strong proficiency in Python and experience building and deploying production-grade backend applications.
- Have practical experience developing LLM-powered applications, including prompt engineering, LLM orchestration, and integration.
- Bring expertise in RAG architectures, embeddings, semantic search, and vector database technologies.
- Have hands-on experience with agentic AI frameworks such as LangChain, LangGraph, or AutoGen.
- Have system design and software architecture skills, including experience developing and scaling cloud-based applications.
- Be able to integrate AI solutions with APIs, enterprise systems, and backend infrastructure.
- Understand AI evaluation methodologies and performance optimization, including accuracy, latency, and cost management.
- Have analytical and problem-solving skills and the ability to take ownership of complex technical projects.
- Healthcare insurance industry experience, particularly in the payer domain, is a strong advantage.
Responsibilities
- Design, architect, and deliver end-to-end LLM-powered applications and agentic workflows using Python.
- Develop RAG pipelines using enterprise data, embeddings, and vector databases.
- Build multi-step AI agents that plan, execute tasks, use external tools, and maintain contextual memory.
- Use LangChain, LangGraph, and AutoGen to orchestrate intelligent workflows.
- Integrate AI applications with APIs, backend services, and cloud-based platforms.
- Develop evaluation strategies to assess accuracy, reliability, scalability, and performance.
- Monitor and optimize latency, operational costs, and solution efficiency.
- Own the development lifecycle from architecture and development through deployment and continuous improvement.
View Full Description & ApplyYou'll be redirected to the employer's site
