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Job Title: Senior AI / LLM Engineer
Locations:
Job Summary
We are seeking a highly skilled Senior AI / LLM Engineer with deep expertise in building production-grade AI applications using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and agentic AI frameworks. The ideal candidate should have strong Python development skills and hands-on experience designing scalable cloud-native AI systems.
This role involves architecting and delivering enterprise-grade AI solutions, integrating intelligent agents with backend systems, and optimizing performance, scalability, and reliability of AI-powered applications.
Required Skills
Job Title: Senior AI / LLM Engineer
Locations:
- Mason, OH
- Plano, TX
- Atlanta, GA
- Cleveland, OH
- Indianapolis, IN
- Iselin, NJ
- Downtown Chicago, IL
- Chicago, IL
- Wallingford, CT
Job Summary
We are seeking a highly skilled Senior AI / LLM Engineer with deep expertise in building production-grade AI applications using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and agentic AI frameworks. The ideal candidate should have strong Python development skills and hands-on experience designing scalable cloud-native AI systems.
This role involves architecting and delivering enterprise-grade AI solutions, integrating intelligent agents with backend systems, and optimizing performance, scalability, and reliability of AI-powered applications.
Required Skills
- Strong Python expertise with experience building and deploying production-grade backend systems
- Hands-on experience developing applications using:
- Large Language Models (LLMs)
- Prompt engineering
- AI orchestration frameworks
- Strong experience with:
- RAG architectures
- Embeddings
- Vector databases
- Experience with agentic AI frameworks such as:
- LangChain
- LangGraph
- AutoGen
- Strong system design and cloud application architecture skills
- Experience building scalable and distributed AI platforms
- Architect and deliver end-to-end LLM-powered applications and agentic AI workflows using Python
- Design and implement RAG pipelines over enterprise datasets using embeddings and vector databases
- Build multi-step intelligent agents with:
- Planning
- Execution
- Tool usage
- Memory capabilities
- Integrate AI solutions with enterprise APIs, backend systems, and cloud platforms
- Define evaluation, monitoring, and optimization strategies for:
- Accuracy
- Latency
- Reliability
- Cost efficiency
- Collaborate with engineering and product teams to deliver scalable AI solutions
- Ensure production readiness, scalability, and operational excellence of AI applications
- Experience with cloud platforms such as AWS, Azure, or Google Cloud Platform
- Familiarity with MLOps, CI/CD, and AI deployment pipelines
- Experience with distributed systems and scalable microservices architectures