Overview
On Site
125000
Full Time
Accepts corp to corp applications
No Travel Required
Unable to Provide Sponsorship
Skills
Kubernetes
Vector DB
LLM Engineer
AI Engineer
Python
LangChain
RAG
Job Details
JOB DESCRIPTION
Looking for an experienced AI Engineer to design, build, and deploy enterprise-grade AI solutions for customers.
The ideal candidate should have hands-on expertise with Retrieval-Augmented Generation (RAG), agentic AI workflows, and LLM-based automation, with the ability to integrate AI systems into complex enterprise environments.
Responsibilities
- Build and optimize RAG pipelines, vector databases, embeddings, and document-processing workflows.
- Design agentic AI systems (tool calling, orchestration, reasoning loops, workflow automation).
- Develop Applied AI solutions that integrate with customer backend systems, APIs, and data sources.
- Implement AI services on Kubernetes, cloud environments, or customer-controlled infrastructure.
- (Good to have) Integrate AI workflows with PLM systems or enterprise knowledge platforms.
- Work directly with customers to deliver high-quality technical implementations, demos, and documentation.
Required Skills
- Strong experience with LLMs, LangChain / LlamaIndex / custom agent frameworks.
- Expertise in Python, vector DBs (Elastic, Milvus, Pinecone, etc.), embeddings, chunking.
- Experience with Kubernetes, Docker, and scalable API deployment.
- Ability to understand customer workflows and translate them into technical solutions.
Nice-to-Have
- Knowledge of PLM, PDM, or enterprise engineering workflows.
- Experience with RAG evaluation, prompt engineering, and grounding strategies.
- Familiarity with enterprise architecture, IAM, SSO, or security constraints.
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.